Fuzzy support vector regression for permeability estimation of petroleum reservoir using well logs

• Autorzy: Moosavi Nastaran , Bagheri Majid , Majid Nabi-Bidhendi , Heidari Reza

Identyfikatory

DOI

10.1007/s11600-021-00700-8

• Języki publikacji: EN

Abstrakty

EN

In this paper we propose a three-step approach to predict permeability. First, by using Electrofacies Analysis (EA), data are classified into several clusters. We take advantage of EA to overcome abrupt changes of permeability which its unpredictability prevents a machine to be learned. EA is also helpful for wells that suffer from core data. Second, fuzzy membership functions are applied on data points in each Electrofacies Log (EL). Third, Support Vector Regression (SVR) is employed to predict permeability using fuzzy clustered data for areas with core missing data. To perform this process, we applied the proposed technique on four well sets of a gas field located in South of Iran; three wells devoted to training and the fourth remained for testing operation. Seven ELs derived using Multi Regression Graph-Based Clustering (MRGC) method. MRGC is able to estimate more appropriate number of clusters without prior knowledge compared to other three algorithms for our case-study area. Then, fuzzy membership functions applied to data. Thereafter, SVR applied to both fuzzy and not-fuzzy ELs. Consequently, the predicted permeability log for both fuzzy and not-fuzzy inputs correlated to real permeability (core data obtained from plugs in laboratory) in the test well. Finally, predicted permeability for each face merged together to make an estimated permeability for the whole test well. The results show that predicted permeability obtained from application of SVR on fuzzy data (FSVR) has a notably better correlation with core data for both clusters individually and the whole data compared to SVR.

Słowa kluczowe

EN

permeability; core data; well logs; support vector regression; fuzzy SVR; heterogeneous reservoirs

PL

przepuszczalność; dane normatywne; geofizyka otworowa; regresja wektora nośnego

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2022
• Tom: Vol. 70, no 1
• Strony: 161--172
• Opis fizyczny: Bibliogr. 48 poz.

Twórcy

autor

Moosavi Nastaran

• Department of Earth Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran

autor

Bagheri Majid

• Institutes of Geophysics, University of Tehran, Tehran, Iran

• https://orcid.org/0000-0003-2059-0194

autor

Majid Nabi-Bidhendi

• Institutes of Geophysics, University of Tehran, Tehran, Iran

autor

Heidari Reza

• Department of Earth Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).