A new method for gas well production splitting based on the principle of superposition of potentials

A new method for gas well production splitting based on the principle of superposition of potentials | 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 A new method for gas well production splitting based on the principle of superposition of potentials Huijie Yang, Zhonglin Wen, Yiwei Xiang, Chenggang Deng, Hui Xu, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7266735/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract As a core part of the refined description of multilayer gas reservoirs, it is difficult for existing methods to quantify the dynamic effects of fluid flow or interference due to interlayer pressure differences in multilayer gas reservoir. In this paper, we propose a new production splitting method based on the principle of superposition of potentials combined with the particle swarm optimization (PSO) algorithm, which aims to better fit the dynamic nature of reservoir fluid flow. The study firstly constructs a three-dimensional spatio-temporal effect fluid potential mathematical model based on the principle of superposition of potentials, and proposes a new method of gas well production splitting based on the principle of superposition of potentials by coupling the potential field calculation of each layer. The results show that the model constructed based on the superposition of potentials has high accuracy, overcomes the discontinuity of the traditional splitting method and the problem of quantifying the interlayer interference, and can dynamically and continuously realize the accurate splitting of the production of each sand body in multilayered collocated gas reservoirs; based on the RFT layered pressure measurement data, the pressure prediction model constructed by ridge regression computes the pressure of the sand body at different times more accurately, and the correlation with the dynamic reserves is good. By taking Sebei No.2 gas field 2 − 1 layer group well Se 5-1-2 as an example for application analysis, it is found that the relative error between the splitting coefficient and the gas production profile data is basically less than 10%, and the error of individual low-production layers is slightly larger; the correlation analysis of dynamic reserves and pressure coefficient of four sands shows that the error of the dynamic reserves calculated based on the method is only 3.82% from the results of the flow pressure calculations. Compared with 106 static pressure test results, the error is less than 10%. gas well production splitting principle of superposition of potentials particle swarm optimization dynamic reserves Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 30 Oct, 2025 Reviewers invited by journal 30 Oct, 2025 Submission checks completed at journal 16 Oct, 2025 First submitted to journal 16 Oct, 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-7266735","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":537535730,"identity":"2592c58a-e349-46a5-8af4-3189cb5d7572","order_by":0,"name":"Huijie Yang","email":"","orcid":"","institution":"PetroChina Qinghai Oilfield Company Research Institute of Exploration and Development","correspondingAuthor":false,"prefix":"","firstName":"Huijie","middleName":"","lastName":"Yang","suffix":""},{"id":537535731,"identity":"bfb3105d-2997-4a57-9e05-96fc9b63f5aa","order_by":1,"name":"Zhonglin Wen","email":"","orcid":"","institution":"PetroChina 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In this paper, we propose a new production splitting method based on the principle of superposition of potentials combined with the particle swarm optimization (PSO) algorithm, which aims to better fit the dynamic nature of reservoir fluid flow. The study firstly constructs a three-dimensional spatio-temporal effect fluid potential mathematical model based on the principle of superposition of potentials, and proposes a new method of gas well production splitting based on the principle of superposition of potentials by coupling the potential field calculation of each layer. The results show that the model constructed based on the superposition of potentials has high accuracy, overcomes the discontinuity of the traditional splitting method and the problem of quantifying the interlayer interference, and can dynamically and continuously realize the accurate splitting of the production of each sand body in multilayered collocated gas reservoirs; based on the RFT layered pressure measurement data, the pressure prediction model constructed by ridge regression computes the pressure of the sand body at different times more accurately, and the correlation with the dynamic reserves is good. By taking Sebei No.2 gas field 2\u0026thinsp;\u0026minus;\u0026thinsp;1 layer group well Se 5-1-2 as an example for application analysis, it is found that the relative error between the splitting coefficient and the gas production profile data is basically less than 10%, and the error of individual low-production layers is slightly larger; the correlation analysis of dynamic reserves and pressure coefficient of four sands shows that the error of the dynamic reserves calculated based on the method is only 3.82% from the results of the flow pressure calculations. Compared with 106 static pressure test results, the error is less than 10%.\u003c/p\u003e","manuscriptTitle":"A new method for gas well production splitting based on the principle of superposition of potentials","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-31 05:02:31","doi":"10.21203/rs.3.rs-7266735/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"88663006668653997115310728466191476087","date":"2025-10-30T13:44:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-30T09:17:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-16T07:32:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Applied Sciences","date":"2025-10-16T05:47:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-applied-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Applied Sciences](https://link.springer.com/journal/42452)","snPcode":"42452","submissionUrl":"https://submission.springernature.com/new-submission/42452/3","title":"Discover Applied Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"abf3c189-5ff6-4bb3-817e-58c91653b67b","owner":[],"postedDate":"October 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-23T17:39:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-31 05:02:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7266735","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7266735","identity":"rs-7266735","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}