Open Access

ARTICLE

Integrated Quality Control and Evaluation Framework for the R&D Process of Waterflooding Sandstone Reservoir Numerical Simulators

Zenghua Zhang^1,2, Yanchun Su^1,2, Zhijie Wei^1,2, Wensheng Zhou^1,2, Chen Liu^1,2, Engao Tang^1,2, Yanhong Wang³, Shanshan Li³, Rui Zhang^3,*
1 State Key Lab of Offshore Oil & Gas Exploitation (abbr. SKLOOGE), Beijing, China
2 CNOOC Research Institute Co. Ltd., Beijing, China
3 Oilfield Production Research Institute, China Oilfield Services Limited, Tianjin, China
* Corresponding Author: Rui Zhang. Email:
(This article belongs to the Special Issue: Progress and Prospects of Hydraulic Fracture Network Morphology Characterization, Flow Simulation and Optimization Technology for Unconventional Oil and Gas Reservoirs)

Energy Engineering https://doi.org/10.32604/ee.2026.077070

Received 01 December 2025; Accepted 09 March 2026; Published online 19 May 2026

Abstract

Addressing the complexity of quality evaluation during the R&D phase of the waterflooding sandstone reservoir numerical simulator (OSIM), this study establishes a comprehensive assessment framework driven by client-side requirements. The novelty of this work lies in the integration of a client-driven 146-indicator hierarchy specifically tailored for iterative simulator R&D. First, a hierarchical software quality evaluation model is constructed, encompassing four primary dimensions and 146 secondary indicators. To mitigate the subjectivity inherent in traditional weight assignment, the Fuzzy Best-Worst Method (FBWM) is employed to determine indicator weights. Subsequently, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is integrated to develop a composite ranking algorithm, coupled with specific protocols for acquiring indicator values were established using an 80-case model library. Finally, the proposed framework is validated using nine iterative versions of OSIM and the Commercial Software (CS). Results indicate that the final OSIM version achieved a superior overall ranking with a composite score of 0.962, surpassing the Commercial Software’s score of 0.944, verifying the effectiveness of the method. The Root Mean Square Error (RMSE) for field water cut was controlled within 1.8%, demonstrating high simulation precision. This methodology exhibits strong universality, offering a scientific reference for the quality assessment of various reservoir simulators, including thermal and chemical flooding.

---

Keywords

Reservoir numerical simulation; software quality evaluation; fuzzy best-worst method; TOPSIS method

---