Remote Sensing and Algorithmic Methods for GOR Monitoring to Improve Gas Production Allocation in Hydrocarbon Production for an oil field in North of Iraq

Remote Sensing and Algorithmic Methods for GOR Monitoring to Improve Gas Production Allocation in Hydrocarbon Production for an oil field in North of Iraq | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Remote Sensing and Algorithmic Methods for GOR Monitoring to Improve Gas Production Allocation in Hydrocarbon Production for an oil field in North of Iraq Farhad A. H. KHOSHNAW, Maha Raoof HAMOUDI, Pshtiwan Jaf This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6463364/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Oct, 2025 Read the published version in Bulletin of Atmospheric Science and Technology → Version 1 posted 11 You are reading this latest preprint version Abstract Satellite imaginings serve as a precise tool for quantifying flared gas at various production sites, thereby enhancing gas production distribution and minimizing flaring activities. This technology enables the monitoring of greenhouse gas emissions, which aids researchers and technical representatives in evaluating the impact of flaring on air pollution, climate change, and environmental degradation. Furthermore, satellite data plays a crucial role in ensuring regulatory compliance and informing policy development by supplying essential information for the enforcement of environmental regulations and the creation of strategies aimed at reducing flaring. It also facilitates cost-effective surveillance of remote or inaccessible areas, allowing for ongoing monitoring that surpasses traditional ground-based methods. The implementation of real-time monitoring and early warning systems allows for the immediate tracking of flaring incidents, promoting timely intervention and mitigation efforts. Additionally, the quantification of flaring through satellite technology can uncover patterns and inefficiencies within gas production processes, guiding companies to invest in technologies that capture gas prior to ignition. This paper integrates a unique algorithm with remote sensing technologies, gas production during oil extraction is estimated via the detection and quantification of associated and non-associated gas flaring. Additionally, the new algorithm enhances the methodology by incorporating temporal information about a flare to refine radiant heat estimates. For cases where predictions of radiant heat are poor, particularly when estimates are high, a cut-off is implemented to revert to the previous model, improving accuracy. With data from two satellites typically providing four observations per night (two measurements each), the algorithm achieves optimal performance by using the mean of the two largest estimated radiant heat values per location per night. This method allows gas-oil-ratio (GOR) monitoring of the Main Limestone reservoir within the studied field in north of Iraq, resulting in better production control and, ultimately, a better calculation of produced dissolved gas with the liquid (oil and water) in the term of gas rate back allocation. The overall constrains included in this work for example, modification of production settings (e.g., a well put in production, shut-in, change in choke size) impact the overall production detected daily. For that purpose, a timely based data from 2018 to 2022 is considered in this work, where the studied field flared in average 95 MMscf/d. In contrast, 2022 flaring averaged only 74 MMscf/d. This decrease implies a significant flaring reduction because of reduction in production. The use of remotely sensed data allows the company a better identification of gas input opportunities from neighbouring fields that could supply the existing power plant. Additionally, the calculated gas rate of the ML is used to estimate ML GOR daily. In 2021, GOR and oil production averaged 873 scf/stb and 149 kstb/d, respectively. In 2022 (January to October), those values are higher for GOR with 926 scf/stb and lower for oil production with 140 kstb/d. In 2022, the ML Field GOR was at its lowest in March with a value of 770 scf/stb before increasing to a maximum of 1040 scf/stb in September and 995 scf/stb in October 2022. While the GOR increases, the field production is decreasing from 148 kstb/d in January to 133 kstb/d in October. The GOR trend has a similar shape to the number of producing wells suggesting that the wells put in production during 2022 produce at a relatively high GOR. So, this work included a model validation of the studied period (between 2018–2022) for 2023, where data from January to June 2023 which consistently recorded has the highest values, while the for the same time average Sankey satellite data reports the lowest, but the allocated gas typically falls in between this confirms the reliability of the approach. Gas production Gas Flare Measuring remote sensing algorithm integration production allocation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 20 Oct, 2025 Read the published version in Bulletin of Atmospheric Science and Technology → Version 1 posted Editorial decision: Revision requested 04 Aug, 2025 Reviews received at journal 14 Jul, 2025 Reviews received at journal 30 Jun, 2025 Reviewers agreed at journal 28 Jun, 2025 Reviewers agreed at journal 26 Jun, 2025 Reviewers agreed at journal 23 Jun, 2025 Reviewers agreed at journal 23 Jun, 2025 Reviewers invited by journal 23 Jun, 2025 Editor assigned by journal 24 Apr, 2025 Submission checks completed at journal 17 Apr, 2025 First submitted to journal 16 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6463364","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":475996141,"identity":"a49904b2-10b0-4a4a-98ae-018042255bcc","order_by":0,"name":"Farhad A. H. KHOSHNAW","email":"data:image/png;base64,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","orcid":"","institution":"Koya University","correspondingAuthor":true,"prefix":"","firstName":"Farhad","middleName":"A. H.","lastName":"KHOSHNAW","suffix":""},{"id":475996142,"identity":"93117a6e-1fa0-4bce-ba83-529df9135e58","order_by":1,"name":"Maha Raoof HAMOUDI","email":"","orcid":"","institution":"University of Kurdistan Hewler","correspondingAuthor":false,"prefix":"","firstName":"Maha","middleName":"Raoof","lastName":"HAMOUDI","suffix":""},{"id":475996143,"identity":"d67d06c5-bb20-4cce-b117-71c47aeb27b0","order_by":2,"name":"Pshtiwan Jaf","email":"","orcid":"","institution":"Koya University","correspondingAuthor":false,"prefix":"","firstName":"Pshtiwan","middleName":"","lastName":"Jaf","suffix":""}],"badges":[],"createdAt":"2025-04-16 12:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6463364/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6463364/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s42865-025-00114-0","type":"published","date":"2025-10-20T16:16:35+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":94490396,"identity":"1aab7bea-2265-4492-8e4b-303db10d8d38","added_by":"auto","created_at":"2025-10-27 17:09:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1678697,"visible":true,"origin":"","legend":"","description":"","filename":"Revisedmanuscript1RemoteSensingandAlgorithmicMethodsforGORMonitoring.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6463364/v1_covered_c1a839a0-88bd-42d0-a528-3fad1efba044.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eRemote Sensing and Algorithmic Methods for GOR Monitoring to Improve Gas Production Allocation in Hydrocarbon Production for an oil field in North of Iraq\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bulletin-of-atmospheric-science-and-technology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bast","sideBox":"Learn more about [Bulletin of Atmospheric Science and Technology](http://www.springer.com/journal/42865)","snPcode":"42865","submissionUrl":"https://submission.nature.com/new-submission/42865/3","title":"Bulletin of Atmospheric Science and Technology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Gas production, Gas Flare Measuring, remote sensing, algorithm integration, production allocation","lastPublishedDoi":"10.21203/rs.3.rs-6463364/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6463364/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSatellite imaginings serve as a precise tool for quantifying flared gas at various production sites, thereby enhancing gas production distribution and minimizing flaring activities. This technology enables the monitoring of greenhouse gas emissions, which aids researchers and technical representatives in evaluating the impact of flaring on air pollution, climate change, and environmental degradation. Furthermore, satellite data plays a crucial role in ensuring regulatory compliance and informing policy development by supplying essential information for the enforcement of environmental regulations and the creation of strategies aimed at reducing flaring. It also facilitates cost-effective surveillance of remote or inaccessible areas, allowing for ongoing monitoring that surpasses traditional ground-based methods. The implementation of real-time monitoring and early warning systems allows for the immediate tracking of flaring incidents, promoting timely intervention and mitigation efforts. Additionally, the quantification of flaring through satellite technology can uncover patterns and inefficiencies within gas production processes, guiding companies to invest in technologies that capture gas prior to ignition. This paper integrates a unique algorithm with remote sensing technologies, gas production during oil extraction is estimated via the detection and quantification of associated and non-associated gas flaring. Additionally, the new algorithm enhances the methodology by incorporating temporal information about a flare to refine radiant heat estimates. For cases where predictions of radiant heat are poor, particularly when estimates are high, a cut-off is implemented to revert to the previous model, improving accuracy. With data from two satellites typically providing four observations per night (two measurements each), the algorithm achieves optimal performance by using the mean of the two largest estimated radiant heat values per location per night. This method allows gas-oil-ratio (GOR) monitoring of the Main Limestone reservoir within the studied field in north of Iraq, resulting in better production control and, ultimately, a better calculation of produced dissolved gas with the liquid (oil and water) in the term of gas rate back allocation. The overall constrains included in this work for example, modification of production settings (e.g., a well put in production, shut-in, change in choke size) impact the overall production detected daily. For that purpose, a timely based data from 2018 to 2022 is considered in this work, where the studied field flared in average 95 MMscf/d. In contrast, 2022 flaring averaged only 74 MMscf/d. This decrease implies a significant flaring reduction because of reduction in production. The use of remotely sensed data allows the company a better identification of gas input opportunities from neighbouring fields that could supply the existing power plant. Additionally, the calculated gas rate of the ML is used to estimate ML GOR daily. In 2021, GOR and oil production averaged 873 scf/stb and 149 kstb/d, respectively. In 2022 (January to October), those values are higher for GOR with 926 scf/stb and lower for oil production with 140 kstb/d. In 2022, the ML Field GOR was at its lowest in March with a value of 770 scf/stb before increasing to a maximum of 1040 scf/stb in September and 995 scf/stb in October 2022. While the GOR increases, the field production is decreasing from 148 kstb/d in January to 133 kstb/d in October. The GOR trend has a similar shape to the number of producing wells suggesting that the wells put in production during 2022 produce at a relatively high GOR. So, this work included a model validation of the studied period (between 2018\u0026ndash;2022) for 2023, where data from January to June 2023 which consistently recorded has the highest values, while the for the same time average Sankey satellite data reports the lowest, but the allocated gas typically falls in between this confirms the reliability of the approach.\u003c/p\u003e","manuscriptTitle":"Remote Sensing and Algorithmic Methods for GOR Monitoring to Improve Gas Production Allocation in Hydrocarbon Production for an oil field in North of Iraq","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-26 13:18:11","doi":"10.21203/rs.3.rs-6463364/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-04T19:21:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-14T12:01:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-30T17:36:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"167005238816413202228700314588587688774","date":"2025-06-28T17:43:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333965565533796940533988383582835898299","date":"2025-06-26T16:50:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"292158050567152796505771544983317983214","date":"2025-06-24T01:27:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61703684313243625673515796080165396789","date":"2025-06-23T11:52:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-23T08:38:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-24T15:21:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-17T13:02:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Bulletin of Atmospheric Science and Technology","date":"2025-04-16T12:06:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bulletin-of-atmospheric-science-and-technology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bast","sideBox":"Learn more about [Bulletin of Atmospheric Science and Technology](http://www.springer.com/journal/42865)","snPcode":"42865","submissionUrl":"https://submission.nature.com/new-submission/42865/3","title":"Bulletin of Atmospheric Science and Technology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f98e1616-0641-4a4b-bb3b-565499191fc6","owner":[],"postedDate":"June 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:33:59+00:00","versionOfRecord":{"articleIdentity":"rs-6463364","link":"https://doi.org/10.1007/s42865-025-00114-0","journal":{"identity":"bulletin-of-atmospheric-science-and-technology","isVorOnly":false,"title":"Bulletin of Atmospheric Science and Technology"},"publishedOn":"2025-10-20 16:16:35","publishedOnDateReadable":"October 20th, 2025"},"versionCreatedAt":"2025-06-26 13:18:11","video":"","vorDoi":"10.1007/s42865-025-00114-0","vorDoiUrl":"https://doi.org/10.1007/s42865-025-00114-0","workflowStages":[]},"version":"v1","identity":"rs-6463364","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6463364","identity":"rs-6463364","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}