Key information

Title
A SYSTEM FOR MANAGEMENT OF CO2 RICH FUME GAS FROM INDUSTRIAL SOURCES TO FINAL DEPOSIT
Application number
20231270
Case type
National
Status
12.01.2026 Innsigelse innkommet og under behandling
Filed
22.11.2023
Effective date
22.11.2023
Publicly available
06.03.2024
Next annual fee due
30.11.2026
Applicant
INTERNATIONAL ENERGY CONSORTIUM AS (NO)
Owner
INTERNATIONAL ENERGY CONSORTIUM AS (NO)
Inventor
Gunnar Myhr (NO)
Granted
12.01.2026
Patent number
349414
Expiry date
22.11.2043

Abstract and drawing

Disclaimer: This text has been machine-scanned and may contain errors – please refer to "Publications" for legally binding content.
This invention relates to, in real time, to the optimized, (AI/ML) intelligent, seamless, selfcorrecting and cost-effective management of fume and/or CO2 gases from industrial source(s) (3) to final deposits in reservoir(s) and/or aquifer(s) (10). AI algorithms are developed related to CO2 leakage and selfcorrection, in a broader system solutions context (13), (15). Both surface and/or offshore (underwater) surveillance systems can be implemented into (13), (15). Special applications related to cost-saving electric power generation, in the context of industrial processes and optimal fume/CO2 disposals, are developed.

Publications

Latest published versionB1

Documents

 Expand Download files (121)
Date
 Date Doc. No. Process Case number In/Out Journal description To/from
09.10.2026 04-03 Innsigelse 2026/00431 UT NPL2 - ABB technology to be used in world’s first open CO2 transport and storage infrastruct....
09.10.2026 04-02 Innsigelse 2026/00431 UT NPL1 - Carbon Dioxide Capture and Storage by the Intergovernmental Panel on Climate Change (....
09.10.2026 04-01 Innsigelse 2026/00431 UT Generelt brev INTERNATIONAL ENERGY CONSORTIUM AS
 09.10.2026 03-01 Innsigelse 2026/00431 UT Bekreftelse til kravstiller/innsiger ZACCO NORWAY AS
09.10.2026 02-12 Innsigelse 2026/00431 UT NPL5 - Harnessing the power of machine learning for carbon capture, utilisation, and storage....
09.10.2026 02-11 Innsigelse 2026/00431 UT NPL4 - Distributed predictive control guided by intelligent reboiler steam feedforward for t....
09.10.2026 02-10 Innsigelse 2026/00431 UT NPL3 - Reinforced coordinated control of coal-fired power plant retrofitted with solvent bas....
09.10.2026 02-09 Innsigelse 2026/00431 UT Innsigelse
09.10.2026 02-08 Innsigelse 2026/00431 UT Engelsk oversettelse av innsigelsen
09.10.2026 02-07 Innsigelse 2026/00431 UT E5 - EP2795055B1
09.10.2026 02-06 Innsigelse 2026/00431 UT E4 - US2010318337
09.10.2026 02-05 Innsigelse 2026/00431 UT E3 - US2023193791
09.10.2026 02-04 Innsigelse 2026/00431 UT E2 - US2011245937
09.10.2026 02-03 Innsigelse 2026/00431 UT E1 - US2023112087
09.10.2026 02-02 Innsigelse 2026/00431 UT D1 - WO2014106265
09.10.2026 02-01 Innsigelse 2026/00431 UT Oversendelse til patenthaver INTERNATIONAL ENERGY CONSORTIUM AS
08.10.2026 01-14 Innsigelse 2026/00431 INN NPL5 - Harnessing the power of machine learning for carbon capture, utilisation, and storage.... ZACCO NORWAY AS
08.10.2026 01-13 Innsigelse 2026/00431 INN NPL4 - Distributed predictive control guided by intelligent reboiler steam feedforward for t.... ZACCO NORWAY AS
08.10.2026 01-12 Innsigelse 2026/00431 INN NPL3 - Reinforced coordinated control of coal-fired power plant retrofitted with solvent bas.... ZACCO NORWAY AS
08.10.2026 01-11 Innsigelse 2026/00431 INN NPL2 - ABB technology to be used in world’s first open CO2 transport and storage infrastruct.... ZACCO NORWAY AS
08.10.2026 01-10 Innsigelse 2026/00431 INN NPL1 - Carbon Dioxide Capture and Storage by the Intergovernmental Panel on Climate Change (.... ZACCO NORWAY AS
08.10.2026 01-09 Innsigelse 2026/00431 INN Innsigelse ZACCO NORWAY AS
08.10.2026 01-08 Innsigelse 2026/00431 INN Engelsk oversettelse av innsigelsen ZACCO NORWAY AS
08.10.2026 01-07 Innsigelse 2026/00431 INN E5 - EP2795055B1 ZACCO NORWAY AS
08.10.2026 01-06 Innsigelse 2026/00431 INN E4 - US2010318337 ZACCO NORWAY AS
08.10.2026 01-05 Innsigelse 2026/00431 INN E3 - US2023193791 ZACCO NORWAY AS
08.10.2026 01-04 Innsigelse 2026/00431 INN E2 - US2011245937 ZACCO NORWAY AS
08.10.2026 01-03 Innsigelse 2026/00431 INN E1 - US2023112087 ZACCO NORWAY AS
08.10.2026 01-02 Innsigelse 2026/00431 INN D1 - WO2014106265 ZACCO NORWAY AS
08.10.2026 01-01 Innsigelse 2026/00431 INN Nytt overprøvningskrav (OP) ZACCO NORWAY AS
 02.10.2026 47-01 Saksbehandling 20231270(349414) UT PT Varsel om betaling av årsavgift for år 4 + (3352) (PT20231270) INTERNATIONAL ENERGY CONSORTIUM AS
 13.01.2026 46-01 Saksbehandling 20231270(349414) UT PT Registreringsbrev nasjonal patent (15) (PT20231270)
24.11.2025 45-01 Saksbehandling 20231270 UT Intention to grant INTERNATIONAL ENERGY CONSORTIUM AS
 19.11.2025 44-05 Saksbehandling 20231270 INN 19_11_2025 Krav på norsk - NO20231270 INTERNATIONAL ENERGY CONSORTIUM AS
 19.11.2025 44-04 Saksbehandling 20231270 INN 19_11_2025 - NO20231270_modified claims CLEAN version INTERNATIONAL ENERGY CONSORTIUM AS
 19.11.2025 44-03 Saksbehandling 20231270 INN 19_11_2025 - NO20231270 - BODY With Annotations - A SYSTEM FOR MANAGEMENT OF CO2 RICH FUME GAS FROM INDUSTRIAL SOURCES TO FINAL DEPOSIT INTERNATIONAL ENERGY CONSORTIUM AS
 19.11.2025 44-02 Saksbehandling 20231270 INN 19_11_2025 - NO20231270 - BODY -clean version - A SYSTEM FOR MANAGEMENT OF CO2 RICH FUME GAS FROM INDUSTRIAL SOURCES TO FINAL DEPOSIT INTERNATIONAL ENERGY CONSORTIUM AS
 19.11.2025 44-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 17.11.2025 43-01 Saksbehandling 20231270 UT Substantive Examination INTERNATIONAL ENERGY CONSORTIUM AS
 16.11.2025 40-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 14.11.2025 42-03 Saksbehandling 20231270 INN 14_11_2025 - NO20231270_modified claims with annotations INTERNATIONAL ENERGY CONSORTIUM AS
 14.11.2025 42-02 Saksbehandling 20231270 INN 14_11_2025 - NO20231270_modified claims CLEAN version INTERNATIONAL ENERGY CONSORTIUM AS
 14.11.2025 42-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 14.11.2025 41-03 Saksbehandling 20231270 INN 14_11_2025 - NO20231270_modified claims with annotations INTERNATIONAL ENERGY CONSORTIUM AS
 14.11.2025 41-02 Saksbehandling 20231270 INN 14_11_2025 - NO20231270_modified claims CLEAN version INTERNATIONAL ENERGY CONSORTIUM AS
 14.11.2025 41-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 13.11.2025 39-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 06.11.2025 38-03 Saksbehandling 20231270 INN 06_11_2025 - NO20231270_modified claims with annotations INTERNATIONAL ENERGY CONSORTIUM AS
 06.11.2025 38-02 Saksbehandling 20231270 INN 06_11_2025 - NO20231270_modified claims CLEAN Version INTERNATIONAL ENERGY CONSORTIUM AS
 06.11.2025 38-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 06.11.2025 37-03 Saksbehandling 20231270 INN 06_11_2025 - NO20231270_modified claims with annotations INTERNATIONAL ENERGY CONSORTIUM AS
 06.11.2025 37-02 Saksbehandling 20231270 INN 06_11_2025 - NO20231270_modified claims CLEAN Version INTERNATIONAL ENERGY CONSORTIUM AS
 06.11.2025 37-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 04.11.2025 36-04 Saksbehandling 20231270 INN JUSTIFICATION FOR THE NON-TRANSITORY CLAIM 18 - NO20231270 Gunnar Myhr
 04.11.2025 36-03 Saksbehandling 20231270 INN 04_11_2025 - NO20231270_CLEAN Claims Gunnar Myhr
 04.11.2025 36-02 Saksbehandling 20231270 INN 04_11_2025 - NO20231270_Claims based on clean copy as of 02_11_2025 - with annotations Gunnar Myhr
 04.11.2025 36-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) Gunnar Myhr
 04.11.2025 35-04 Saksbehandling 20231270 INN JUSTIFICATION FOR THE NON-TRANSITORY CLAIM 18 – NO20231270 INTERNATIONAL ENERGY CONSORTIUM AS
 04.11.2025 35-03 Saksbehandling 20231270 INN 04_11_2025 - NO20231270_CLEAN Claims INTERNATIONAL ENERGY CONSORTIUM AS
 04.11.2025 35-02 Saksbehandling 20231270 INN 04_11_2025 - NO20231270_Claims based on clean copy as of 02_11_2025 - with annotations INTERNATIONAL ENERGY CONSORTIUM AS
 04.11.2025 35-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 03.11.2025 33-05 Saksbehandling 20231270 INN Rev 02_11_2025 - New Non-trasitory claim INTERNATIONAL ENERGY CONSORTIUM AS
 03.11.2025 33-04 Saksbehandling 20231270 INN NO20231270 Revised independent claim 1 and non-transitory claim (claim 18) with annotations and complete set of clean claims INTERNATIONAL ENERGY CONSORTIUM AS
 03.11.2025 33-03 Saksbehandling 20231270 INN 02_11_2025 - NO20231270_Claims_clean_copy INTERNATIONAL ENERGY CONSORTIUM AS
 03.11.2025 33-02 Saksbehandling 20231270 INN 02_11_2025 - New Claim 1- NO20231270 with annotations INTERNATIONAL ENERGY CONSORTIUM AS
 03.11.2025 33-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 02.11.2025 34-04 Saksbehandling 20231270 INN Rev 02_11_2025 - New Non-trasitory claim with annotatioons INTERNATIONAL ENERGY CONSORTIUM AS
 02.11.2025 34-03 Saksbehandling 20231270 INN 02_11_2025 - NO20231270_Claims_clean_copy INTERNATIONAL ENERGY CONSORTIUM AS
 02.11.2025 34-02 Saksbehandling 20231270 INN 02_11_2025 - New Claim 1- NO20231270 with annotations INTERNATIONAL ENERGY CONSORTIUM AS
 02.11.2025 34-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 30.10.2025 32-04 Saksbehandling 20231270 INN Comprehensive Reply to Office Aaction as of August 27_2025 - NO20231270 - September 11_2025 INTERNATIONAL ENERGY CONSORTIUM AS
 30.10.2025 32-03 Saksbehandling 20231270 INN 30_10_2025 - New Claim 1 with annotations - NO20231270 INTERNATIONAL ENERGY CONSORTIUM AS
 30.10.2025 32-02 Saksbehandling 20231270 INN 30_10_2025 - A New Independent Claim (non-transitory memory claim) - with annotations - NO20231270 INTERNATIONAL ENERGY CONSORTIUM AS
 30.10.2025 32-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 02.10.2025 31-01 Saksbehandling 20231270 UT PT Varsel om betaling av første årsavgift (3317) (PT20231270) INTERNATIONAL ENERGY CONSORTIUM AS
 11.09.2025 30-02 Saksbehandling 20231270 INN Comprehensive Reply to Office Aaction as of August 27_2025 - NO20231270 - September 11_2025 INTERNATIONAL ENERGY CONSORTIUM AS
 11.09.2025 30-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 27.08.2025 29-02 Saksbehandling 20231270 UT PT report 03:02:52
27.08.2025 29-01 Saksbehandling 20231270 UT Substantive Examination INTERNATIONAL ENERGY CONSORTIUM AS
 17.03.2025 02-01 Endring av fullmektig 2025/03440 UT GH Forespørsel APACE IP AS
 07.03.2025 28-03 Saksbehandling 20231270 INN Inquiry - DOES THE PAPER HETLAND (2009) REPRESENT RELEVANT PRIOR ART TO NO20231270 - NO INTERNATIONAL ENERGY CONSORTIUM AS
 07.03.2025 28-02 Saksbehandling 20231270 INN Hetland (2009) INTERNATIONAL ENERGY CONSORTIUM AS
 07.03.2025 28-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 07.03.2025 02-01 Endring av fullmektig 2025/03439 UT GH Forespørsel INTERNATIONAL ENERGY CONSORTIUM AS
 05.03.2025 01-02 Endring av fullmektig 2025/03440 INN Patentstyret_20231270 APACE IP AS
 05.03.2025 01-01 Endring av fullmektig 2025/03440 INN Generell henvendelse APACE IP AS
 04.03.2025 01-02 Endring av fullmektig 2025/03439 INN PoA - NO20231270 INTERNATIONAL ENERGY CONSORTIUM AS
 04.03.2025 01-01 Endring av fullmektig 2025/03439 INN Generell henvendelse INTERNATIONAL ENERGY CONSORTIUM AS
 28.02.2025 02-01 Endring av fullmektig 2025/02881 UT GH Forespørsel APACE IP AS
 27.02.2025 27-03 Saksbehandling 20231270 INN 20231270_Claims_clean_copy APACE IP AS
 27.02.2025 27-02 Saksbehandling 20231270 INN 20231270_Claims (Marked Up) APACE IP AS
 27.02.2025 27-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) APACE IP AS
 27.02.2025 26-04 Saksbehandling 20231270 INN Rp_NO20231270_P372NO00 APACE IP AS
 27.02.2025 26-03 Saksbehandling 20231270 INN 20231270_Claims (Marked Up) APACE IP AS
 27.02.2025 26-02 Saksbehandling 20231270 INN 20231270_Claims (Clean) APACE IP AS
 27.02.2025 26-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) APACE IP AS
 27.02.2025 01-02 Endring av fullmektig 2025/02881 INN GPoA_IEC_Apace APACE IP AS
 27.02.2025 01-01 Endring av fullmektig 2025/02881 INN Generell henvendelse APACE IP AS
 30.12.2024 25-01 Saksbehandling 20231270 UT Substantive examination INTERNATIONAL ENERGY CONSORTIUM AS
 01.10.2024 24-04 Saksbehandling 20231270 INN 177276 Letter to the NIPO AWA NORWAY AS
 01.10.2024 24-03 Saksbehandling 20231270 INN 177276 Amended claims NO20231270 01102024 AWA NORWAY AS
 01.10.2024 24-02 Saksbehandling 20231270 INN 177276 Amended claims - auxiliary claims NO20231270 01102024 AWA NORWAY AS
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 27.02.2024 14-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 27.02.2024 13-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 26.02.2024 15-02 Saksbehandling 20231270 INN Slakter regjeringens kraftløfte Finansavisen INTERNATIONAL ENERGY CONSORTIUM AS
 26.02.2024 15-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 21.02.2024 12-02 Saksbehandling 20231270 INN SV_ Norwegian Patent Application No_ 20231270 - Response to Officee Action - AWA ref_ 177276 - Expedited Examination (1)
21.02.2024 12-01 Saksbehandling 20231270 INN SV_ Norwegian Patent Application No_ 20231270 - Response to Officee Action - AWA ref_ 177276 - Expedited Examination
21.02.2024 11-01 Saksbehandling 20231270 INN SV_ Norwegian Patent Application No_ 20231270 - Response to Officee Action - AWA ref_ 177276 - Expedited Examination
10.02.2024 10-03 Saksbehandling 20231270 INN Claims - NO20231290 with Annotations- pdf ONSAGERS AS
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02.02.2024 07-01 Saksbehandling 20231270 UT 20231270_1809279_PT 08 Eng INTERNATIONAL ENERGY CONSORTIUM AS
 19.01.2024 06-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 15.01.2024 05-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 20.12.2023 04-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 12.12.2023 03-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 22.11.2023 02-03 Saksbehandling 20231270 INN søknadskvittering INTERNATIONAL ENERGY CONSORTIUM AS
 22.11.2023 02-02 Saksbehandling 20231270 INN Overføring av rettigheter - Patentstyret - An AI Optimized -- INTERNATIONAL ENERGY CONSORTIUM AS
 22.11.2023 02-01 Saksbehandling 20231270 INN Korrespondanse (Hovedbrev inn) INTERNATIONAL ENERGY CONSORTIUM AS
 22.11.2023 01-05 Saksbehandling 20231270 INN Figure - An AI Optimized Gunnar Myhr
 22.11.2023 01-04 Saksbehandling 20231270 INN Description - An Ai Optimized Gunnar Myhr
 22.11.2023 01-03 Saksbehandling 20231270 INN Claims - An AI Optimized Gunnar Myhr
 22.11.2023 01-02 Saksbehandling 20231270 INN Abstract - An AI Optimized Gunnar Myhr
 22.11.2023 01-01 Saksbehandling 20231270 INN Søknadsskjema Patent Gunnar Myhr

Description, claims and drawings

Disclaimer: This text has been machine-scanned and may contain errors – please refer to "Publications" for legally binding content. Description
3494141This invention is related to AI algorithms, and the intelligent and seamless fume gas handling from combustion source(s) to final deposit in reservoir(s) and/or aquifer(s).Introduction and DefinitionsClimate awareness, the Paris Accord and the latest COP28, to take place in UAE as of November/December of 2023, are all strong voices to limit the release of particularly CO2 into the atmosphere. In this context the capture and storage of CO2, from industrial combustion processes, are of paramount importance.All “references”, terms, definitions, and phrases related to all aspects mentioned in the "Introduction and Definitions", "Prior Art", “Invention”, “Industrial Case Study” sections and in the figure, also apply to, form the basis of, and are incorporated into the invention represented by this document.Some general elements like comments covering e. g. definitions, real time control systems, AI, etc. follow, to some degree, what is stated in our previous documents NO20220294 and NO20230704 (“self-reference”).Some definitions are intentionally cross referenced.“Ship”, “vessel”, “vehicle”, “car”, “truck”, “device”, “object”, “human”, “individual”, “diver”, “activity”, “submarine” are synonymous terms. Any surface or underwater objects can be manned, unmanned, remotely operated or autonomous.“Storage”, “tank”, “(mobile) truck”, “rail tank”, “train”, “vessel”, ”ship”, ”pipeline”, “container” are synonymous terms that can contain and/or transport any combinations of gases, hydrocarbons, and/or fumes/CO2 in a stationary and/or mobile capacity, both onshore and/or offshore.The term "offshore" represents any device, structure, at least one of the components (1-15, S1-S11, C1-C11) or installation located on, within or at the bottom (subsea) of water.Equivalently, "onshore" represents any device, at least one of the components (1-15, S1-S11, C1-C11) or structure located not on, within or under water (subsea).The term “installation”, “platform”, “structure”, “units” are synonymous concepts.The statement “at least one of” means, from a set of variables, activities or processes (synonymous terms) [a1, a2, …an] either a1, a2, …or an isolated (single activity) or any combination(s) among the variables. The term “at least one of” and “any combinations of” are synonymous. 3494142“Cable”, “(power) line”, “connection” and “wire” are synonymous terms.“Crude oil”, “petroleum components”, “refined products”, “non-refined petroleum” and “oil” are synonymous terms.The term "gas" represents any combination of the gasses methane, ethane, propane, butane and the terms Natural Gas Liquids (NGL) and condensate. The concept "natural gas" is a mixture of methane and varying amounts of other higher alkanes. Condensate is NGL (Natural Gas Liquids) and hexane, heptane and octane. NGL is LPG (Liquid Petroleum Gas) and ethane and pentane. LPG is a mix of propane and butane. Natural gas can contain CO2, N2 and sulfide in addition to "gas". "Gas" and "natural gas" are synonymous terms.“LNG” – Liquified Natural Gas, represents liquefied “natural gas”.Hydrocarbons (HC) or “HC products” (synonymous terms) can be any combinations of gas and oil, in any combination of solid, liquid or gaseous states.“Fuel” or “fuel supply” is/are any combinations of HC and/or any combustible substance. “Grid” and “network” are synonymous terms.“Source” and “supply” are synonymous terms.“Power source”, “energy source”, electric power”, “power arrangement” and “power” are synonymous terms.The terms “fume”, “fume gas supply”, "fume gas(es)", "flue gases", "gas mixture" and “CO2” are defined as synonymous terms.“CO2” can represent the gas (CO2) in various concentrations and with or without any pollutions and/or any other atmospheric gases.The terms "inject" and reinject" are synonymous terms.“Element(s)”, “component(s)”, “unit(s)” are synonymous.The terms “reservoir” and “aquifer” are defined as synonymous terms and represent both “storage” and HC supply source.Some further definitions are stated in the text to follow. 3494143Prior ArtEP2795055 represents the closest prior art. The invention is related to systems for offshore or land based industrial activities which use for feedstock or produce gas, crude oil and/or refined petroleum products, and provide reservoir injection of fume gases.The “Langskip” project represents a terminal in Øygarden, outside Bergen, for the reception of CO2 from outside sources for the injection into the “Smeaheia” aquifer offshore. Planned operational start up is during 2024. For details see e.g.;https://ccsnorway.com/no/status-fra-langskip-prosjektet-per-juni-2023/ https://www.regjeringen.no/en/topics/energy/landingssider/ny-side/sporsmal-og-svar-omlangskip-prosjektet/id2863902/WO2020107600 discloses a smart pipeline. When the pipeline leaks,the pipeline automatically closes a corresponding valve. The smart pipeline control center receives various signals transmitted by the smart pipeline remote control device and the flow sensor and can close the leakage protection valve.WO2020107600 Teaches a method involving transmitting a number of commands from a terminal to a portable data carrier e.g. chip card, and processing the commands on the data carrier. The pipeline-based parameter is dynamically adjusted by the carrier or by the terminal.WO2014106265A2 (D1) represents a gas turbine system, including a combustor configured to combust an oxidant and a fuel in the presence of an exhaust gas diluent to produce combustion products. The system is limited to power plant/turbine control (“source”), with no disclosure of CO₂/fume gas transport, storage, compression, injection, dual controllers, or multi-modal sensing.Rolnick, D. et al. Tackling Climate Change with Machine Learning, ACM Computing Surveys, Vol.55, No.2, Article 42, (February 2022) (D4); Is a survey of ML opportunities; mentioning “monitoring” and “imaging,” but it does not disclose e.g. actuation, compressors, or any closed-loop CO2/fume gas related process control.None of the prior art teach enabling features related to e.g. the novel, (AI/ML) intelligent seamless process flows from source to deposit of fume gases outlined by this invention. In this respect e.g. dual communications from the at least one transportation subsystem, and intelligent monitoring and self-correcting features of the total system, or the unexpected lowcost in certain industrial applications are inventive. 3494144InventionA system is a group of interacting or interrelated elements or components (synonymous) that act or are interconnected according to a set of rules or mechanisms to form a unified whole. A system is surrounded by its boundaries.The objective technical problem to be solved by the invention, is the development of an optimized, (AI/ML) intelligent, seamless, self-correcting and the cost-effective management of fume and/or CO2 gases from industrial source(s) to final deposits in reservoir(s) and/or aquifer(s). AI algorithms are developed related to CO2 leakage and in a broader system solutions context. Special applications related to cost-saving hydrocarbon fueled electric power generation, in the context of industrial processes and optimal fume/CO2 disposal, are also within the scope of the invention.With reference to fig.1, at least one of the components (1-15) and/or at least one of (S1-S11) and/or at least one of (C1-C11) can be powered by at least one external grid (not shown) and/or at least one internal grid (not shown) independent of the electric power (4), generated within the system.Subsystem AWith reference to fig.1, the subsystem (A), “the generation “ or “the source module” or “generation module” (synonymous terms) is represented by a fuel supply (1). (1) can be, partially or fully, a HC substance or any other combustible material(s). “Other combustible materials” can be, but not limited to, coal, wood, organic materials and/or waste materials. (2) is a combustion process. (3) represents a combustion process (2) in an industrial context (3). This can be, but not limited to, the production of fertilizers, cement, HC refinery processes, electric power generation. The combustion process can occur offshore or onshore. In combination with HC production or on a standalone basis.The combustion process (3) can generate steam and/or heat. Often are HC products, fully or partially, the fuel in this context, but not necessarily. The steam and/or heat can be produced from, but not limited to, at least one boiler unit, and/or at least one gas turbine, and/or at least one steam turbine, and/or at least one combined cycle power unit, or any other combustible material in a combustion process (2). Heat and/or steam can be end- products by itself. 3494145Combined cycle power plants (3), can use any combinations of (e.g.) gas turbines (or gas engines, gas engines can be fueled by any type of HC), furnace/heat exchangers and steam turbine(s), see e.g. https://www.ge.com/gas-power/products/hrsg for details. The transformation of energy in (3) can be converted with the use of at least one generator (not shown), but not necessarily, into electric power (4).The at least one fume gas flow (5) from (2) and/or (3) can be, but not necessarily, be treated by at least one carbon capture (CC) unit (6). Various CC approaches can be labeled as e.g. post-combustion, oxy-fuel combustion or phase separation. The various techniques which can be utilized are among chemical (amine) solvents, physical solvents, physical absorbents, membrane separation processes, chemisorption, chemical bonding, phase separation. For elaborations, see e.g. “Sustainable Carbon Capture Technologies and Applications”, ed. Suleman, H. et al, ISBN 9780367755140, CRC Press, 2022.If an oxy-fuel process is applied, (6) can be omitted and (1a) represents oxygen, of various concentrations, which ca be combined with (1).(A) can be represented by a storage facility (7).The most basic version of (A) constitute the boundary; at least one fuel supply into the system (1), at least one combustion process (2) and (5), fume gases out of the subsystem. More advanced subsystems include any combinations of (3), (4), (6) and (7) in addition to the most basic version (1, 2, 5). If an electric power system is included (4), (4a) and/or (4b) can represent output of the subsystem (A). The electric power (4) can be delivered to an external grid (4a) and/or be delivered to an internal grid (4b) to supply e.g. the industrial process (11) of subsystem (B) and/or to at least one of the other components (1-10) and/or at least one of (S1-S11) and/or at least one of (C1-C11). If the produced power (4) is exclusively delivered to an external grid (4a), (3) and (4) will most likely deliver at (near to) capacity. If the power (4) is exclusively powering the internal grid (4b), the control systems (15) and/or (13), interconnected by the processing units, (or any other component) (14) and (12), respectively, will have to measure electric demand from e.g. (11) (or any other component) and produce accordingly by (3). If the power (4) is partially supplying the external grid (4a) and partially (the residual) is delivered to the internal grid (4b), the real time control system (15) and/or (13) has to measure the demand from e.g. (11) (or any other component) and produce accordingly by (3). The same occurs when the industrial process (11) (or any other component) is exclusively powered by an external grid (4a), the control systems (15) and/or (13) has to measure the demand from e.g. (11) (or any other component) and the external grid (4a) has 3494146to deliver accordingly.For details related to advanced power-grid monitoring systems combine i.a. load-balancing, power-supply monitoring, metering functions, protection, supervision of power quality and disturbances, transient monitoring, and to enable efficient power delivery, see e.g.: https://www.mouser.com/pdfdocs/Solar-Maxim-Power_Grid_Monitoring.pdf https://www.dnv.com/services/grid-code-compliance-measurements-72067https://www.dnv.com/services/grid-code-compliance-measurements-72067 https://unipower.se/products-and-services/power-quality-management-system/pq-secure/The at least one sensor (S1…S7) and the accompanying at least one communication unit (C1…C7), see following text for details, will be connected to at least one processing unit (12) and controlled by at least one real time control and guidance unit (13).The total system can include more than one subsystem (A). (5) can be released into the atmosphere in case of emergencies. The at least one real time control system (15) and/or (13) can be integrated into at least one unit.SensorsThe at least one sensor (S1-S11) can, but are not limited to, detect (quality and quantity to) pressure, temperature, heat (infrared), frequencies (sound, light), stress, strain, liquid (level), fume, CO2, gas (concentrations), one or two phase fluid flows, relative and absolute humidity, movements, motion, represent cameras, low light cameras, infrared cameras, GPS trackers, telephones, Internet of Things (IoT). Such sensors can be, but are not limited to, analog or digital electronic, electro - mechanical, optical or of ultrasound types. The at least one sensor (S1-S11) are connected by at least one wire or wireless communication unit (C1-C11).In an underwater context, (not shown) the at least one sensor, can constitute a (passive) hydrophone represented by, but not limited to, among a fiberoptic hydrophone (FOH), inductive or not, FOH array, aperture array (LWWAA), a magnetic anomaly detection (MAD) system represented by, but not limited to, magnetometers, gradiometers, a processing unit, which can, but is not limited to, guide the power to the at least one sensor (not shown), can cipher (encrypt), decipher (decrypt) or code signals to and from the at least one sensor, but not necessarily.The at least one sensor can detect signals above 20 kHz, below 20 kHz, below 1 kHz or below 100 Hz. Signal detection in the range 0 < f < 100 Hz is emphasized. 3494147To locate and estimate the trajectory or movements of any object by detecting and measuring e.g. the Extremely Low Frequencies radiated by targets, under noisy conditions, in real time, additional algorithms can be added to (13) and/or (15). This includes stationary or moving targets, both onshore and offshore in shallow and deep- sea waters.One such approach or algorithm, but not limited to, is the use of a Progressive (Bayes) Updated Extended Kalman Filter (PUEKF) model. Traditional Kalman filters utilize a onestep observation update. The concept of progressive Bayes is to insert pseudo time series, and gradually introduce observation information to solve the problem of a too narrow Extended Kalman Function. PUEKF is a new nonlinear filtering algorithm based on the progressive updating idea of progressive Bayes and extended Kalman filters. For further details, see e. g.: Zhang, J-W, et al. Real-time localization for underwater equipment using an extremely low frequency electric field. Defense Technology, https://doi.org/10.1016/j.dt.2022.06.014 , 2022. Zhou, S. et al. Progressive Kalman Filter and Its Application in Magnetic Target Tracking. 2019 4th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), DOI: 10.1109/ICMCCE48743.2019.00086, 2019.Hanebech, U. D. et al. Progressive Bayes: A New Framework for Nonlinear State Estimation. Proceedings of SPIE - The International Society for Optical Engineering, DOI:10.1117/12.487806, April 2003.Birsan, M. Measurement of the extremely low frequency (ELF) magnetic field emission from a ship. Measurement Science and Technology, Volume 22, Number 8, 2011.Subsystem CWith reference to fig. 1, the subsystem (C), “the transportation module” or “transporting subsystem” (synonymous terms), is represented by the at least one fume gas (supply) (5), which can be transported and/or stored by the means of at least one of or any combinations of (8); represented by at least one of, but not limited to;Storage, pipeline, (mobile) truck, vehicle, container, tank, rail tank, train, vessel, ship, reservoir, aquifer or any other subterraneous, onshore and/or offshore storage or transportation facility.(5) can also represent fume gases within a pipeline (8).(7) and (8) are synonymous terms, but (7) tend(s) to be stationary.The at least one sensor S7 and/or S8 and the accompanying of at least one communication unit C7 and/or C8, will communicate with the at least real time one control and guidance system (15) and/or (13), or (15) or (13), where (15) or (13) can communicate with each other or be integrated into at least one unit. The input/output boundaries of (C) are (5). The total 3494148system can be represented by more than one subsystem (C). This enables the seamless feature or abilities of the total system.The at least one (7) of subsystem (A), the at least one (8) of subsystem (C) and the at least one (7) of subsystem (B) can be integrated into at least one storage unit. In this context (A) and (B) will be integrated into one unit.The “total system” is represented by (A), (B) and (C). The “total system” can represent at least one component. In this case (A), (B) and (C) are integrated.Subsystem BWith reference to fig.1, the subsystem (B) or “the storage subsystem” can be represented by at least one storage unit (7) and/or (8). The at least one such unit, (7) and/or (8), can be located at subsystem (A), and/or (B) and/or (C). At least one pressure devise or compressor system (9) will provide the at least one fume gas (5) with adequate pressure enabling the at least one (5) to reach final deposit in at least one reservoir and/or aquifers (10).Output of (B) is the final deposit of fume and/or CO2 within at least one storage facility (10). (10) is most likely at least one reservoir and/or aquifer offshore. The at least one compressor unit (9) and at least one pipeline (not shown), underwater facilities (not shown), at least one injection well (not shown) will facilitate the process or processes. For elaborations see e.g. Carter, J. Petroleum Engineering Handbook, ISBN: 9781639874262, Murphy & Moore, 2023 or NO332044.(10) can (also) be a HC producing reservoir. In this case HC will represent input to the subsystem, labelled (1*). (1*) can be stabilized offshore or onshore, but not necessarily.The at least one sensor (S7…S11) and the accompanying at least one communication unit (C7…C11), will be connected to at least one processing unit (14) and controlled by at least one real time control and guidance unit (15). The total system can include more than one subsystem (B). Fuel (1) can be, partially or fully, transported or represent an output of (B) and/or the total system by any means of transportation, including, but not limited to at least one of (mobile) truck, rail tank, train, vessel, ship, pipeline, storage. 3494149Real-time Control and Guidance SystemsOverall coordination of the total system (A) and (B), where (C) can be integrated into (A) and/or (B) and/or (A) and (B) can be integrated and the at least one of (1-11), is/are executed by at least one processing units (12) and/or (14), which are governed by the at least one real time control and guidance system (13) and/or (15).(12) and (14) can be integrated into at least one unit. (13) and (15) can be integrated into at least one unit.Real-time control requires controllers to capture all the significant target activities and to deliver their responses as swiftly as possible so that system performance is never degraded. In Advanced Industrial Control Technology, Peng Zhang, 2010, ISBN: 978-1-4377-7807-6, https://www.sciencedirect.com/book/9781437778076/advanced-industrial-controltechnology#book-info, structure and requirements to real-time control systems are outlined, excerpts (chapter 1.2.1, line 7):“A control operation is a series of events or actions occurring within system hardware and software to give a specific result. A real-time control system is a system in which the correctness of a result depends not only on its logical correctness but also on the time interval in which the result is made available. The following three standards give the definition of a real-time control operation, and an industrial control system in which all thecontrol operations occur in real-time qualifies as a real-time control system:(1) Reliable operation execution - the operation execution must be stable, and it must be repeatable.(2) Determined operation deadline - any control operation needs time to execute.(3) Predictable operation result -the result for any control operation must be predictable.” Artificial intelligence (AI) technologies will advance or support the next generation of control systems.Based on e.g. combinations of, but not limited to, Model Predictive Control, (MPC), Proportional Integral Derivative (PID), Deep Reinforcement Learning (DRL), three characteristics of AI-based controllers can be emphasized;1. Learning: DRL-based controllers learn by methodically and continuously practicing (machine learning). 349414102. Delayed gratification: DRL-based controllers can learn to recognize sub-optimal behavior in the short term, which enables the optimization of gains in the long term.3. Non-traditional input data: DRL-based controllers manage the intake and are able evaluate sensor information that automated systems cannot.The enablement of e.g. DRL-based control systems to a process facility, require, but are not limited to, the following steps in delivering a DRL-based controls:1. Preparation of a companion simulation model for the (AI) brain,2. Design and training of the (AI) brain,3. Assessment of the trained (AI) brain,4. Deployment.For further reading, see e.g. :https://www.controleng.com/articles/evolution-of-controlsystems-with-artificial-intelligence/In this context the AI brain(s) is/are, but not limited to, to be trained to, at least one of; foresee, forecast, predict, simulate or otherwise, related to the total process flow, represented by at least one of (1-10, 1-11), but not limited to;- sudden or unexpected changes in fuel supply (1), power demand from (11),- supply and/or delivery status to any connected grid or electric power (4a) and/or (4b), - reservoir status (10),- weather status,- technical and maintenance status to the various components constituting the total system, represented by at least one of (1-11),- Surface and/or underwater activities related to, but not limited to, human behavior, humans, ships, manned, unmanned devices, remotely operated or autonomous vehicles, submarines (not shown), 34941411Additional algorithms integrated into (13) and/or (15)Process flowProcess flow optimization represents streamlining e.g. at least one of components (1-10, 1-11) to enhance its efficiency, productivity, and overall performance.Detecting CO2 leakage involving leveraging AI and/or machine learning (ML) techniques to monitor, identify, and respond to the escape of CO2 in the various components e.g. (1-10, 1-11). The main objective is to prevent potentially hazardous situations and minimize environmental impact.Detailed solutions can be derived from at least one of, but not limited to;- Deep Learning for Anomaly Detection in Hydroelectric Power Plants. https://ieeexplore.ieee.org/document/10218027The use of Deep Neural Network with Logistic Regression to classify various types of failures, and a Recurrent Long Short-Term Memory neural network (LSTM) with Autoencoder to classify various flaws.-Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. https://edx.netl.doe.gov/smart/-Anomaly Detection for Hydroelectric Power Plants: a Machine Learning-based Approach. https://ieeexplore.ieee.org/document/10218027Represents the use of anomaly detection and explainability algorithms to supplement Decision Support System insights in Predictive Maintenance and Root Cause Analysis.Leak detectionLeak detection and prevention in fume/CO2 pipelines (5) are critical for the safety and efficiency of CC systems, e.g. (5-7).Some strategies and technologies which can be used, but are not limited to;-Measurement, Monitoring, and Verification (MMV) Technologies, see ieeexplore.ieee.org. -Acoustic Emission Techniques.Acoustic emission techniques can be used to detect leaks in CO2 pipelines. These techniques work by detecting the high-frequency sound waves produced by a leak. See e.g. ieeexplore.ieee.org. 34941412-E-RTTM Based Leak Detection System: An E-RTTM (Extended Real Time Transient Model) based leak detection system can support the safe management of the CO2 transport pipeline’s operations. See e.g.; us.krohne.com.-Machine Learning Model and Strategy for Fast and Accurate Detection of Leaks in Water Supply Network,ML models are used to detect leaks in the Water Distribution Network (WDN). Water pressure data under leaking versus non-leaking conditions can be generated with holistic WSN simulation code EPANET considering factors such as the fluctuating user demands. The results indicate that Artificial Neural Network (ANN), a supervised ML model, can accurately classify leaking versus non-leaking conditions. See e.g. jipr.springeropen.com-Rock On: Scientists Use AI to Improve Sequestering Carbon Underground,is an AI-based tool named U-FNO to help lock up e.g. CO2 in porous rock formations. See e.g. https://blogs.nvidia.com/blog/2022/04/08/ai-improves-carbon-sequestration/Selv-correctionThe outlined AI/ML algorithms can be designed to correct their own predictions over time, and improve their accuracy. This can be achieved through a process of continuous learning and adjustment based on the comparison of predicted and actual outcomes. E.g. in Q-learning, a form of reinforcement learning, a self-correcting algorithm has been proposed to balance the overestimation of the single estimator used in conventional Q-learning and the underestimation of the double estimator used in Double Q-learning.In the context of CO2 leak detection and prevention, such self-correcting algorithms could potentially be used to continuously improve the accuracy of predictions related to leak detection and the effectiveness of prevention measures. As the algorithm(s) receive feedback about its performance, it could adjust its parameters to improve future predictions and recommendations. In this way, the at least one component (1-10, 1-11) become(s) more accurate and reliable over time. For elaborations, see e.g. https://www.annualreviews.org/doi/10.1146/annurev-statistics-031219-041220 https://www.ijcai.org/Proceedings/2017/0483.pdfAdvances in Neural Information Processing Systems 33 (NeurIPS 2020)Edited by: H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin ISBN: 9781713829546 34941413Industrial Case StudyCO2 removalCO2 is a naturally occurring diluent or pollutant in oil and gas reservoirs. CO2 can react with H2S and H2O to make corrosive compounds that threaten steel pipelines and/or components. Thus, it is critical that pipeline levels of CO2 are no more that 2%-3%. Well head natural gas can contain as much as 30% CO2. For details see e.g.;https://www.ametekpi.com/-/media/ametekpi/files/resource-center/white-paper-library/theanalysis-of-carbon-dioxide-in-natural-gas.pdf?la=en&revision=e8e400f5-f9c6-46fd-b65b-8c3659610ccb&hash=A8FD7066E113A33F5829A6E67DCD63CAAs an example, the natural gas produced from the Sleipner West field contains up to 9 % CO2. In order to meet the required export specifications and the customers’ requirements, this has to be reduced to a maximum of 2.5 %. This threshold represents the ceiling specified in the Troll gas sales agreements.The process of separating CO2 from natural gas can e.g. take place by a simple distillation process, by bringing amine and natural gas together in a tank at high pressure and moderate temperature. The amine binds to CO2 and separates out at the bottom of the tank.This is then transferred to a new tank where the pressure is lower and the temperature higher. The CO2 will then be separated and passed on from the tank to the CO2 injection system. See e.g.; https://www.equinor.com/no/news/archive/2008/04/23/CarbonStorageStartedOnSnhvit In general, there are three basic methods of separating CO2 from a gas stream;• Separation with sorbents/solvents,• Separation with membrane,• Separation with cryogenic distillation,“Amine scrubbing technology was established over 60 years ago in the oil and chemical industries, for removal of H2S and CO2 from gas streams. Commercially, it is the most wellestablished of the techniques available for CO2 capture …”See e.g. https://www.co2captureproject.org/pdfs/3_basic_methods_gas_separation.pdf Other references of CO2 removal by e.g. distillation or membrane, see; https://iopscience.iop.org/article/10.1088/1757-899X/755/1/012052 34941414https://www.sciencedirect.com/science/article/abs/pii/S1875510021005825An Industrial Example with Extreme Cost EffectivenessWith the removal of CO2 from the natural gas, within commercial limits, LNG can be produced and exported.LNG is a clear, colorless and non-toxic liquid which forms when natural gas is cooled to -162 ºC. The cooling process shrinks the volume of the gas by 600 times, making it commercially to store and ship safely. For elaborations of LNG processes, se e.g.;How Does an LNG Plant Work? (econnectenergy.com)LNG and natural gas processing plants | Linde Engineering (linde-engineering.com)An integrated LNG production facility with self-generated CO2 free electricity, is proposed along the following steps, with reference to fig.1, including the features outlined by this invention;1. We have a locally produced natural gas (1*), as input into subsystem (B). It is stabilized and excess CO2 are removed in the at least one unit (11) and the CO2 (5) is injected into the at least one (10), and the at least one residual (1) is/are provided as fuel (1) and/or made into LNG in the at least one unit (11).2. Any production wells, offshore and/or subsea infrastructure costs are outside of the boundary.3. With reference to the at least one subsystem (A), the at least one fuel (1), as output from the at least one (11), represents in principle zero transportation costs, and it is in gaseous condition. It can be priced marginally.4. At least one power source, preferably a combined cycle power plant (3), at least one Carbon Capture unit (6) within a subsystem (A), are located in close vicinity to the deposit module (B), represented by (9) and (10). (A) can be located onshore, offshore, on a barge, a fixed structure, subsea, represent an FPSO, or a simple vessel (ship) in a fixed position. Both a barge and a ship can be permanently positioned to a pier, jetty land bridge etc. In these latter applications no costly turrets, swivels or any moving transmissions of pipes and/or cables are necessary.5. (1) and (5) can be transported to and from (A) to (B) by at least one pipeline each. 349414156. Electric power (4a) and/or (4b) are transported to the at least one (11) for the separation of CO2 from the at least one natural gas (1*) and the cooling of natural gas into LNG. (11) represent both natural gas – CO2 separation and LNG production.7. The fume/CO2 (5) from the natural gas separation unit (11) can be injected into (10) together [same pipeline structure (not shown)] with (5) from (C) and/or (A) or by separate pipeline structures.The most cost effective is to utilize the existing pipeline infrastructure.8. Processing units (14) and/or (12) and real time control systems (15) and/or (13) are integral parts of an integrated LNG production facility with self-generated CO2 free electricity. (15) and/or (13) can represent a master/slave relationship or the one can be superior to the other in a hierarchy or they are integrated into at least one unit.The unit (11) is not limited to the production of LNG. It can produce at least one of fuel, HC, or gas and/or a residual that is made into fuel or gas or HC.An Example of a Favorable Total System;At least one system for collecting and storing carbon, comprising:a generation subsystem (A) that produces a fume gas (5);a transporting subsystem (C) that receives the fume gas (5);a storage subsystem (B) including a reservoir and/or aquifer (10) that receives the fume gas (5) from the transporting subsystem (C) and stores the fume gas (5) or CO2 from the fume gas (5);characterized bya first control system (13) including a first processing unit (12) that monitors and controls the generation subsystem;a second control system (15) including a second processing unit (14) that monitors and controls the storage subsystem,wherein at least one of the first control system (13) and the second control system (15) monitors the transporting system (C), the first control system (13) is in communication with the second control system (15), and the first control system (13) and the second control system (15) provide coordinated real-time control of the system. 34941416The system for collecting and storing is/are characterized by the first control system (13) and the second control system (15) use artificial intelligence (AI) and/or machine learning (ML) to monitor, identify, and respond to CO2 leaks.The system for collecting and storing carbon is/are characterized by the generation subsystem (A) includes a combustion module (3) that utilizes a combustion process and produces the fume gas (5) and at least one generator (4) driven by the combustion module (3) that produces electric power.The system for collecting and storing carbon characterized by the electric power generated by the at least one generator (4) is transported to and utilized by the storage subsystem (B).The system for collecting and storing carbon is/are characterized by the storage subsystem (B) includes a removal unit (11) that removes CO2 from a material.The system for collecting and storing carbon according is/are characterized by the removal unit (11) removes the CO2 from a natural gas to produce a fuel and the fuel output by the removal unit (11) is used by the combustion module (3).The system for collecting and storing carbon is/are characterized by the system is a fuel or gas production facility, the removal unit (11) produces the fuel or gas and/or a residual that is made into the fuel or gas or HC.The system for collecting and storing carbon is/are characterized by the fuel or gas produced by the storage subsystem (B) is transported to the generation subsystem (A) through the transporting subsystem (C) and the fume gas generated by the generation subsystem (A) is transported to the storage subsystem (B) through the transporting subsystem (C).The system for collecting and storing carbon is/are characterized by the electric power produced by the generation subsystem (A) is used by the removal unit (11) to separate CO2 from the natural gas and for cooling of the natural gas into LNG.The system for collecting and storing carbon is/are characterized by the generation subsystem (A) includes at least one of a carbon capture unit (6) and a storage facility (7) to control a flow of the fume gas and/or CO2 to the transporting subsystem.The system for collecting and storing carbon is/are characterized by the storage subsystem (B) includes a compressor to provide the fume gas adequate pressure to reach a final deposit in 34941417the reservoir and/or aquifer (10) and/or a storage facility to control a flow of the fume gas and/or CO2 from the transporting subsystem (C).The system for collecting and storing carbon according is/are characterized by the first control system (13) and the second control system (15) exhibit a master/slave relationship.The system for collecting and storing carbon s/are characterized by the first control system (13) and the second control system (15) are integrated in one unit.The system ca be characterized by the fuel (1) can be, partially or fully, transported or represent an output of (B) and/or the total system by any means of transportation, including, but not limited to, at least one of (mobile) truck, rail tank, train, vessel, ship, pipeline, storage.
Claims
34941418Claims1. A system for management of fume gas from industrial sources to final deposit, comprising:- a generation subsystem (A) configured to receive a fuel (1) and produce a fume gas stream (5);- a transporting subsystem (C) configured to receive and convey the fume gas stream (5); and - a storage subsystem (B) including at least one reservoir and/or aquifer (10) configured to receive and store CO2 from the fume gas stream (5);characterized by:- a first control system (13) including a first processing unit (12) configured to monitor and control the generation subsystem (A);- a second control system (15) including a second processing unit (14) configured to monitor and control the storage subsystem (B);- the first control system (13) being in communication with the second control system (15) to provide coordinated real-time adaptive control of the system;- at least one of the first control system (13) and the second control system (15) being configured to monitor the transporting subsystem (C); and- a sensor and communication network comprising at least one sensor S1-S11 and at least one communication unit C1 -C11 that provide real-time data; and- the first control system (13) and/or the second control system (15) implementing at least one intelligent control algorithm to detect, foresee, forecast, predict or simulate the system by:(i) monitoring, identifying, and responding to CO2 leaks;(ii) sudden or unexpected changes in fuel supply (1);(iii) controlling compressor (9) for compression and injection into the reservoir and/or aquifer (10);(iv) reservoir and/or aquifer status (10);(v) supply and/or delivery status to any connected power grid or electric power (4a) and/or (4b);(vi) technical and maintenance status of various components of the system (1-11);(vii) correcting predictions over time and improving the accuracy of various components of the system (1-11);34941419(viii) surface and/or underwater activities related to human behavior, humans, ships, manned, unmanned devices, remotely operated or autonomous vehicles, or submarines; or (ix) any combination of (i)-(viii).2. The system according to claim 1, characterized bythe generation subsystem (A) includes a combustion module (2, 3) that utilizes a combustion process and produces the fume gas (5) and at least one generator (4) driven by the combustion module that produces electric power.3. The system according to claim 2, characterized bythe electric power generated by the at least one generator (4) is transported to and utilized by the storage subsystem (B).4. The system according to claim 3, characterized bythe storage subsystem (B) includes a removal unit (11) that removes CO2 from a material.5. The system according to claim 4, characterized bythe removal unit (11) removes the CO2 from a natural gas to produce fuel (1) to be used by the combustion module (2, 3).6. The system according to claim 5, characterized bythe fuel produced by the removal (unit) in the storage subsystem (B) is transported to the generation subsystem (A) through the transporting subsystem (C) and the fume gas generated by the generation subsystem (A) is transported to the storage subsystem (B) through the transporting subsystem (C).7. The system according to claim 6, characterized bythe electric power-produced by the generation subsystem (A) is used by the removal unit (11) to separate CO2 from the natural gas and for cooling of the natural gas into LNG.349414208. The system according to any one of the previous claims, characterized bythe generation subsystem (A) includes at least one of a carbon capture unit (6) and a storage facility (7) to control the flow of fume gas in form of CO2 to the transporting subsystem (C).9. The system according to any one of the previous claims, characterized bythe storage subsystem (B) includes a compressor (9) to provide the fume gas adequate pressure to reach a final deposit in the reservoir and/or aquifer (10) and/or a storage facility (7) to control a flow of the fume gas in form of CO2 from the transporting subsystem (C).10. The system according to any one of the previous claims, characterized bythe first control system (13) and the second control system (15) exhibit a master/slave relationship.11. The system according to any one of the previous claims, characterized bythe first control system (13) and the second control system (15) are integrated in one unit.12. The system according to any one of the previous claims, characterized bythe fuel (1) can be, partially or fully, transported or represent by any means of transportation, including at least one of truck, rail tank, train, vessel, ship, pipeline, storage.13. The system according to any one of the previous claims, characterized bythe at least one fume gas flow (5) from combustion modules (2, 3) and can be treated by at least one carbon capture unit (6).14. The system according to any one of the previous claims, characterized by the system is located offshore wherein the fuel (1) is locally produced by at least one reservoir (10) which is represented by a HC producing reservoir (1*).3494142115. The system according to any one of the previous claims, characterized bythe at least one reservoir (10) can be represented by a HC producing reservoir (1*) and/or at least one fume gas (5) to reach final deposit in at least one reservoir and/or aquifers (10).16. The system according to any one of the previous claims, wherein the at least one of the various components of the system (1-11) and the first control systems (13) and/or the second control system (15) with respective processing unit (12, 14)and/or (S1-S11) and/or (C1-C11), is/are located onshore and/or offshore, characterized by the at least one of the components (1-15) and/or (S1-S11) and/or (C1-C11) can be powered by at least one external grid and/or at least one internal grid independent of the electric power generator (4), generated within the system by combustion modules (2,3) and/or generator (4),- and/or the electric power can be delivered to an external grid (4a) and/or be delivered to an internal grid (4b) to supply at least one of the components (1-15) and/or (S1-S11) and/or (C1-C11),- and/or the electric power generator (4) is exclusively powering the internal grid (4b), the control system (15) and/or (13), will have to measure electric demand from at least one of the components (1-15) and/or (S1-S11) and/or (C1-C11) and produce electric power accordingly by the combustion module (2, 3) and/or generator (4),- and/or the electric power generator (4) is partially supplying the external grid (4a) and partially is supplying to the internal grid (4b), the control system (15) and/or (13) has to measure the electric demand from at least one of the components (1-15) and/or (S1-S11) and/or (C1-C11) and produce electric power accordingly by the combustion module (2, 3) and/or generator (4),- and/or the at least one of the components (1-15) and/or (S1-S11) and/or (C1-C11) is/are exclusively electrically powered by an external grid (4a), the control system (15) and/or (13) has to measure the electric demand from at least one of the components (1-15) and/or (S1-S11) and/or (C1-C11) and the external grid (4a) has to supply electric power accordingly.17. A non-transitory memory storing an executable program for system for management of fume gas from industrial sources to final deposit, executed by:34941422a first control system (13) monitoring and controlling a generation subsystem (A) configured to receive a fuel (1) and produce a fume gas stream (5),and- a second control system (15) monitoring and controlling a storage subsystem (B) including at least one reservoir and/or aquifer (10) configured to receive and store CO2 from the fume gas stream (5), wherein- the first control system (13) being in communication with the second control system (15) to provide coordinated real-time adaptive control of the system;and- at least one of the first control system (13) and the second control system (15) is monitoring a transporting subsystem (C) configured to receive and convey the fume gas stream (5);and- processing data from at least one sensor S1-S11 and at least one communication unit C1-C11;- implementing at least one intelligent control algorithm to detect, foresee, forecast, predict or simulate the system by:(i) monitoring, identifying, and responding to CO2 leaks;(ii) sudden or unexpected changes in fuel supply (1);(iii) controlling compressor (9) for compression and injection into the reservoir and/or aquifer (10);(iv) reservoir and/or aquifer status (10);(v) supply and/or delivery status to any connected power grid or electric power (4a) and/or (4b);(vi) technical and maintenance status of various components of the system (1-11);(vii) correcting predictions over time, and improving the accuracy of various components of the system (1-11);(viii) surface and/or underwater activities related to, but not limited to, human behavior, humans, ships, manned, unmanned devices, remotely operated or autonomous vehicles, or submarines; or(ix) any combination of (i)-(viii).34941423Krav1. Et system for håndtering av røykgass fra industrielle kilder til endelig deponi, omfattende:et genererings delsystem (A) konfigurert til å motta et brensel (1) og produsere en røykgassstrøm (5);et transport delsystem (C) konfigurert til å motta og transportere røykgass-strømmen (5); oget lagringsd delsystem (B) som inkluderer minst ett reservoar og/eller akvifer (10) konfigurert til å motta og lagre CO₂ fra røykgass-strømmen (5);kjennetegnet ved:et første kontrollsystem (13) som inkluderer en første prosesseringsenhet (12) konfigurert til å overvåke og styre genererings delsystemet (A);et andre kontrollsystem (15) som inkluderer en andre prosesseringsenhet (14) konfigurert til å overvåke og styre lagrings delsystemet (B);at det første kontrollsystemet (13) er i kommunikasjon med det andre kontrollsystemet (15) for å gi koordinert, sanntidsadaptiv styring av systemet;at minst ett av det første kontrollsystemet (13) og det andre kontrollsystemet (15) er konfigurert til å overvåke transport delsystemet (C); oget sensor- og kommunikasjonsnettverk som omfatter minst én sensor S1–S11 og minst én kommunikasjonsenhet C1–C11 som leverer sanntidsdata; ogat det første kontrollsystemet (13) og/eller det andre kontrollsystemet (15) implementerer minst én intelligent styringsalgoritme for å detektere, forutse, predikere eller simulere systemet ved:(i) overvåking, identifisering og respons på CO₂-lekkasjer;(ii) plutselige eller uventede endringer i brenselforsyningen (1);(iii) styring av kompressor (9) for komprimering og injeksjon i reservoar og/eller akvifer (10);(iv) status for reservoar og/eller akvifer (10);34941424(v) forsyning og/eller leveringsstatus til ethvert tilkoblet kraftnett eller elektrisk kraft (4a) og/eller (4b);(vi) teknisk og vedlikeholdsmessig status for ulike komponenter i systemet (1–11);(vii) korrigering av prediksjoner over tid og forbedring av nøyaktigheten til ulike komponenter i systemet (1–11);(viii) overflate- og/eller undervannsaktiviteter relatert til menneskelig atferd, mennesker, skip, bemannede eller ubemannede enheter, fjernstyrte eller autonome fartøy eller ubåter; eller(ix) enhver kombinasjon av (i)–(viii).2. Systemet ifølge krav 1, kjennetegnet ved at genererings delsystemet (A) inkluderer en forbrenningsmodul (2, 3) som benytter en forbrenningsprosess og produserer røykgassen (5), og minst én generator (4) drevet av forbrenningsmodulen som produserer elektrisk kraft.3. Systemet ifølge krav 2, kjennetegnet ved at den elektriske kraften generert av minst én generator (4) transporteres til og brukes av lagrings delsystemet (B).4. Systemet ifølge krav 3, kjennetegnet ved at lagrings delsystemet (B) inkluderer en fjerningsenhet (11) som fjerner CO₂ fra et materiale.5. Systemet ifølge krav 4, kjennetegnet ved at fjerningsenheten (11) fjerner CO₂ fra naturgass for å produsere brensel (1) som skal brukes av forbrenningsmodulen (2, 3).6. Systemet ifølge krav 5, kjennetegnet ved at brenselet produsert av fjerningsenheten i lagrings delsystemet (B) transporteres til genererings delsystemet (A) via transport delsystemet (C), og røykgassen produsert av genererings delsystemet (A) transporteres til lagrings delsystemet (B) via transport delsystemet (C).7. Systemet ifølge krav 6, kjennetegnet ved at den elektriske kraften produsert av genererings delsystemet (A) brukes av fjerningsenheten (11) til å separere CO₂ fra naturgass og til nedkjøling av naturgassen til LNG.8. Systemet ifølge ethvert foregående krav, kjennetegnet ved at genererings delsystemet (A) inkluderer minst én av en karbonfangstenhet (6) og et lagringsanlegg (7) for å kontrollere flyten av røykgass i form av CO₂ til transport delsystemet (C).349414259. Systemet ifølge ethvert foregående krav, kjennetegnet ved at lagrings delsystemet (B) inkluderer en kompressor (9) for å gi røykgassen tilstrekkelig trykk til å nå et endelig deponi i reservoar og/eller akvifer (10) og/eller et lagringsanlegg (7) for å kontrollere flyten av røykgass i form av CO₂ fra transport delsystemet (C).10. Systemet ifølge ethvert foregående krav, kjennetegnet ved at det første kontrollsystemet (13) og det andre kontrollsystemet (15) har et master/slave-forhold.11. Systemet ifølge ethvert foregående krav, kjennetegnet ved at det første kontrollsystemet (13) og det andre kontrollsystemet (15) er integrert i én enhet.12. Systemet ifølge ethvert foregående krav, kjennetegnet ved at brenselet (1) kan, delvis eller fullt, transporteres eller representeres ved ethvert transportmiddel, inkludert minst én av lastebil, jernbanetank, tog, fartøy, skip, rørledning, lagring.13. Systemet ifølge ethvert foregående krav, kjennetegnet ved at minst én røykgass-strøm (5) fra forbrenningsmoduler (2, 3) kan behandles av minst én karbonfangstenhet (6).14. Systemet ifølge ethvert foregående krav, kjennetegnet ved at systemet er lokalisert offshore, hvor brenselet (1) produseres lokalt av minst ett reservoar (10) som er representert ved et HC-produserende reservoar (1*).15. Systemet ifølge ethvert foregående krav, kjennetegnet ved at minst ett reservoar (10) kan være representert ved et HC-produserende reservoar (1*), og/eller at minst én røykgass-strøm (5) når endelig deponi i minst ett reservoar og/eller akvifer (10).16. Systemet ifølge ethvert foregående krav, hvor minst én av ulike komponenter i systemet (1–11) og det første kontrollsystemet (13) og/eller det andre kontrollsystemet (15) med respektive prosesseringsenheter (12, 14) og/eller (S1–S11) og/eller (C1– C11) er plassert på land og/eller offshore, kjennetegnet ved at minst én av komponentene (1–15) og/eller (S1–S11) og/eller (C1–C11) kan forsynes av minst ett eksternt nett og/eller minst ett internt nett uavhengig av den elektriske kraftgeneratoren (4), generert i systemet av forbrenningsmoduler (2, 3) og/eller generator (4),og/eller at den elektriske kraften kan leveres til et eksternt nett (4a) og/eller til et internt nett (4b) for å forsyne minst én av komponentene (1–15) og/eller (S1–S11) og/eller (C1–C11),34941426og/eller at den elektriske kraftgeneratoren (4) utelukkende forsyner det interne nettet (4b), og kontrollsystemet (15) og/eller (13) må måle elektrisk behov fra minst én av komponentene (1– 15) og/eller (S1–S11) og/eller (C1–C11) og produsere elektrisk kraft deretter via forbrenningsmodulen (2, 3) og/eller generator (4),og/eller at den elektriske kraftgeneratoren (4) delvis forsyner det eksterne nettet (4a) og delvis det interne nettet (4b), og kontrollsystemet (15) og/eller (13) må måle elektrisk behov fra minst én av komponentene (1–15) og/eller (S1–S11) og/eller (C1–C11) og produsere elektrisk kraft deretter,og/eller at minst én av komponentene (1–15) og/eller (S1–S11) og/eller (C1–C11) utelukkende er elektrisk forsynt av et eksternt nett (4a), og kontrollsystemet (15) og/eller (13) må måle elektrisk behov fra minst én av komponentene (1–15) og/eller (S1–S11) og/eller (C1–C11), og det eksterne nettet (4a) må levere elektrisk kraft deretter.17. Et håndgripelig lagringsmedium som lagrer et program som kan utføres for et system for håndtering av røykgass fra industrielle kilder til endelig deponi, utført av:et første kontrollsystem (13) som overvåker og styrer et genererings delsystem (A) konfigurert til å motta et brensel (1) og produsere en røykgass-strøm (5),oget andre kontrollsystem (15) som overvåker og styrer et lagrings delsystem (B) som inkluderer minst ett reservoar og/eller akvifer (10) konfigurert til å motta og lagre CO₂ fra røykgassstrømmen (5),hvordet første kontrollsystemet (13) er i kommunikasjon med det andre kontrollsystemet (15) for å gi koordinert, sanntidsadaptiv styring av systemet;ogminst ett av det første kontrollsystemet (13) og det andre kontrollsystemet (15) overvåker et transport delsystem (C) konfigurert til å motta og transportere røykgass-strømmen (5);ogprosesserer data fra minst én sensor S1–S11 og minst én kommunikasjonsenhet C1–C11;og34941427implementerer minst én intelligent styringsalgoritme for å detektere, forutse, predikere eller simulere systemet ved:(i) overvåking, identifisering og respons på CO₂-lekkasjer;(ii) plutselige eller uventede endringer i brenselforsyningen (1);(iii) styring av kompressor (9) for komprimering og injeksjon i reservoar og/eller akvifer (10);(iv) status for reservoar og/eller akvifer (10);(v) forsynings- og/eller leveringsstatus til ethvert tilkoblet kraftnett eller elektrisk kraft (4a) og/eller (4b);(vi) teknisk og vedlikeholdsmessig status for ulike komponenter i systemet (1–11);(vii) korrigering av prediksjoner over tid og forbedring av nøyaktigheten til ulike komponenter i systemet (1–11);(viii) overflate- og/eller undervannsaktiviteter relatert til, men ikke begrenset til, menneskelig atferd, mennesker, skip, bemannede, ubemannede enheter, fjernstyrte eller autonome fartøy eller ubåter; eller(ix) enhver kombinasjon av (i)–(viii).
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Patent classes

IPC classesF01K 23/00F02C 3/00F02C 1/00E21B 43/00F02C 9/00G06N 20/00CPC classesF01K 23/00F02C 3/00F02C 1/00E21B 43/00F02C 9/00G06N 20/00

Citations

WO 2014106265 A2 (A2)US 2021148246 A1 (A1)EP 3968111 A1 (A1)DAVID ROLNICK ET AL., Tackling Climate Change with Machine Learning, ACM Computing Surveys, Vol. 55, No. 2, Article 42. Publication date: February 2022 ()

Applicants, owners and inventors

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INTERNATIONAL ENERGY CONSORTIUM AS
INTERNATIONAL ENERGY CONSORTIUM AS

Org. number: 912678296

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c/o Gunnar Myhr Putten 50 1676 KRÅKERØY NO (FREDRIKSTAD Municipality, Østfold county)Org. number: 912678296Inventors
Gunnar Myhr
Putten 50 1676 KRÅKERØY NO (FREDRIKSTAD Municipality, Østfold county)

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InnsigelseReceived: 08.10.2026 NIPO's case No.: 2026/00431Current status: Under behandling. Brevveksling/utgående brev i saken
OpponentGASSNOVA SF
GASSNOVA SF

Org. number: 991627626

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Opponent's agentZACCO NORWAY AS Postboks 488 0213 OSLO NO (OSLO Municipality, Oslo county)
Org. number: 982702887Reference: OP511618NO00

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