Automation of 3-D Regression Method and Newton-Raphson Algorithm for Computing Petrophysical Exponents and Residual Oil Saturation: A Case Study of the

Ifanegan, Ayomide Samson; Enikanselu, Pius Adekunle; Olisa, Benson Akinbode; Abiola, Olubola

doi:10.22050/ijogst.2025.494509.1724

Automation of 3-D Regression Method and Newton-Raphson Algorithm for Computing Petrophysical Exponents and Residual Oil Saturation: A Case Study of the "FAS"-Field, Offshore Niger Delta.

Document Type : Research Paper

Authors

Ayomide Samson Ifanegan ¹

Pius Adekunle Enikanselu ²

Benson Akinbode Olisa ³

Olubola Abiola ⁴

¹ 1 Assistant Lecturer, Department of Applied Geophysics, Federal University of Technology Akure, PMB 704, Nigeria

² 2 Professor, Department of Applied Geophysics, Federal University of Technology Akure, PMB 704, Nigeria

³ 3 Reader, Department of Applied Geophysics, Federal University of Technology Akure, PMB 704, Nigeria

⁴ 4 Reader, Department of Applied Geophysics, Federal University of Technology Akure, PMB 704, Nigeria

10.22050/ijogst.2025.494509.1724

Abstract

Residual oil saturation (Sor) estimation is a critical component of reservoir development and enhanced oil recovery (EOR) projects. Traditionally, Sor is estimated using the Archie method, in which accuracy strongly depends on petrophysical exponents, including the tortuosity factor (a), cementation factor (m), and saturation exponent (n). However, the conventional method assumes a homogeneous rock formation, rendering it ineffective and unreliable in shaly sand reservoirs. Additionally, field-based determination of petrophysical exponents and Sor is often difficult and time-consuming. This study addresses these limitations by developing a Python-based application that integrates a three-dimensional (3-D) regression technique with the Newton–Raphson algorithm. The application was tested using well logs from eight wells and statistically validated against core Sor data from the FAS Field, Offshore Niger Delta. Results indicated that the tortuosity factor (a) ranged from 0.28 (FAS-06) to 2.73 (FAS-04), the cementation factor (m) varied from 0.43 (FAS-06) to 4.11 (FAS-04), and the saturation exponent (n) ranged from 0.71 (FAS-04) to 8.59 (FAS-05). Correspondingly, Sor ranged from 0.11 (FAS-05) to 0.99 (FAS-06). The percentage deviation of the computed Sor relative to the core data ranged from 5% (FAS-01) to 27% (FAS-02) for the 3-D regression method and from 3% (FAS-03) to 52% (FAS-02) for the Newton–Raphson technique. The results indicate that the 3-D regression method is more efficient and reliable for computing petrophysical exponents and Sor in the study area.

Highlights

· Field-based petrophysical exponents were computed using the Newton–Raphson algorithm and a three-dimensional regression method.

· Residual fluid saturation was calculated from the derived petrophysical exponents using Archie’s equation.

· The accuracy of the developed application was evaluated using two reservoirs (A and B) delineated from eight wells in the FAS Field, Niger Delta.

Keywords

Enhanced-oil recovery, Homogeneous rock formation, Newton&ndash

Raphson algorithm

Subjects

Hydrocarbon Reservoirs Management

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