Estimation of water saturation based on optimized models in tight gas sandstone reservoirs: A case study of Triassic Xujiahe Formation in northwestern Sichuan Basin

Estimation of water saturation based on optimized models in tight gas sandstone reservoirs: A case study of Triassic Xujiahe Formation in northwestern Sichuan Basin | 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 Estimation of water saturation based on optimized models in tight gas sandstone reservoirs: A case study of Triassic Xujiahe Formation in northwestern Sichuan Basin Xiaoyong Xia, Bing Han, Bing Xie, Qiang Lai, Yuexiang Wang, Shaowu Zhu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4007402/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Water saturation estimation faced a great challenge in tight gas sandstone reservoirs because of the effect of pore structure and strong heterogeneity to rock resistivity. The classic Archie’s equation cannot be always well used. To quantify the effect of pore structure to rock resistivity in tight gas sandstones, taking the Triassic Xujiahe Formation of northwestern Sichuan Basin as an example, 35 core samples were recovered and applied for resistivity experiments in laboratory under the simulated formation temperature and pressure environment, and 18 of them were simultaneously applied for nuclear magnetic resonance (NMR) and high-pressure mercury injection (HPMI) experimental measurements. Relationships between rock pore structure and resistivity parameters were analyzed. The results clearly illustrated that cementation exponent ( m ) and saturation exponent ( n ) were heavily affected by pore structure. Rocks with superior pore structure contained relative higher cementation exponent and lower saturation exponent, and vice versa. Afterwards, we raised a parameter of pore size index, which was defined as the ration of macropore and micropore percentage contents, to reflect rock pore structure, and established a model to calculate optimal saturation exponent from NMR data. Meanwhile, various cementation exponent prediction model was also raised by combining with porosity and irreducible water saturation ( S wirr ). By combining with calculated cementation exponent and saturation exponent, we optimized the Archie’s equation to predict water saturation in our target tight gas sands. Field examples illustrated that the predicted cementation exponent and saturation exponent matched well with core-derived results. The absolute errors between predicted cementation exponent and saturation exponent with core-derived results were lower than 0.05 and 0.07, separately. By using the optimized Archie’s equation, water saturations were precisely predicted from well logging data in our target tight gas sandstone reservoirs. Water saturation NMR logging Tight gas sandstone Pore structure Optimized models Full Text Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Minor revisions 03 Apr, 2024 Reviewers agreed at journal 19 Mar, 2024 Reviewers invited by journal 19 Mar, 2024 Editor invited by journal 17 Mar, 2024 Editor assigned by journal 06 Mar, 2024 First submitted to journal 04 Mar, 2024 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-4007402","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":281520273,"identity":"10c37a26-e5e6-46a6-bfbb-9bfd216cad48","order_by":0,"name":"Xiaoyong 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The classic Archie\u0026rsquo;s equation cannot be always well used. To quantify the effect of pore structure to rock resistivity in tight gas sandstones, taking the Triassic Xujiahe Formation of northwestern Sichuan Basin as an example, 35 core samples were recovered and applied for resistivity experiments in laboratory under the simulated formation temperature and pressure environment, and 18 of them were simultaneously applied for nuclear magnetic resonance (NMR) and high-pressure mercury injection (HPMI) experimental measurements. Relationships between rock pore structure and resistivity parameters were analyzed. The results clearly illustrated that cementation exponent (\u003cem\u003em\u003c/em\u003e) and saturation exponent (\u003cem\u003en\u003c/em\u003e) were heavily affected by pore structure. Rocks with superior pore structure contained relative higher cementation exponent and lower saturation exponent, and vice versa. Afterwards, we raised a parameter of pore size index, which was defined as the ration of macropore and micropore percentage contents, to reflect rock pore structure, and established a model to calculate optimal saturation exponent from NMR data. Meanwhile, various cementation exponent prediction model was also raised by combining with porosity and irreducible water saturation (\u003cem\u003eS\u003c/em\u003e\u003csub\u003ewirr\u003c/sub\u003e). By combining with calculated cementation exponent and saturation exponent, we optimized the Archie\u0026rsquo;s equation to predict water saturation in our target tight gas sands. Field examples illustrated that the predicted cementation exponent and saturation exponent matched well with core-derived results. The absolute errors between predicted cementation exponent and saturation exponent with core-derived results were lower than 0.05 and 0.07, separately. 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