Analysis of Enrichment-Controlling Factors and Seismic Prediction of Gas-Rich Zones in Tight Sandstone Gas Reservoirs: A Case Study from the Second Member of the Qianfoya Formation in Bazhong Area, Sichuan Basin
4 affiliations
- 1Yangtze University , , ,
- 2No.10 Oil Production Plant of Changqing Oilfield , ,
- 3China University of Petroleum (East China) , , ,
- 4Sinopec Exploration Company , ,
Abstract
The Qianfoya Formation in the Bazhong area of the Sichuan Basin comprises a typical tight sandstone formation characterized by low porosity, low permeability, and strong reservoir heterogeneity. Effective reservoirs in this region are relatively thin, and seismic responses between gas-bearing layers and dry layers differ only slightly. These geological complexities create substantial challenges for predicting tight sandstone reservoirs and gas-rich zones, which necessitate targeted and effective geological and geophysical prediction research. Therefore, taking the Second Member of the Qianfoya Formation (Qian-2 Member) as the research object, this study utilizes multiwell logging, mud logging, and 3D seismic data sets. We first analyze the geological characteristics of the target interval to clarify the primary controlling factors of tight sandstone gas reservoir enrichment. Based on these factors, we establish an effective geophysical prediction workflow tailored for gas-bearing tight sandstone reservoirs. This method is further applied to predict gas-rich zones within the Qian-2 Member. The study concludes that (1) the main controlling factors for tight gas reservoir enrichment in the Qian-2 Member are sedimentary facies distribution, reservoir-cap rock conditions, and fracture distribution. (2) Prestack simultaneous inversion integrated with rock physics analysis enables effective sand-body identification. Rock physics analysis identifies P-wave impedance (Zp) and S-wave impedance (Zs) as the sensitive parameter pair for sand bodies. A sand-body factor prediction model is then constructed via coordinate rotation. Sensitive parameters are derived from prestack simultaneous inversion, and the sand-body factor is calculated from the prediction model. High positive values of the sand-body factor are used to predict sand-body distribution. (3) Based on near- and far-offset seismic comparison, the dominant amplitude–frequency method is used to extract the gas-bearing prediction attributes, whose positive anomalies effectively identify gas-bearing intervals. (4) A multifactor prediction framework combining sand bodies, gas-bearing properties, and fractures is adopted for gas-rich zones prediction. The results show that gas-rich zones in the Qian-2 Member are concentrated in the middle and upper submembers, and the predicted favorable zones are mainly distributed around faults. (5) This study establishes a workflow for predicting gas-rich zones of tight sandstone gas reservoirs via multifactor geological superposition analysis. Well-seismic calibration verifies its applicability, providing a methodological foundation and practical reference for the comprehensive prediction of favorable targets in similar tight sandstone gas reservoirs.
Related
- Mechanisms of Water-Lock Removal by a Nanoemulsion/Mud Acid Composite System in Low-Permeability Sandstone Reservoirs: Insights from Pore-Scale Characterization in the MB Block
- Diagenetic Evolution of Deep Tight Sandstone Reservoirs in the Lower Jurassic Strata of the Kuqa Depression, Tarim Basin
- Mechanical Prediction of Shale Oil Reservoirs Based on Micromechanical Characterization, Machine Learning, and Upscaling Model
- Characterization of Macro-Micro Heterogeneity in Shale Reservoirs Based on Full-Diameter Core CT Scanning─A Case Study of Jurassic Lianggaoshan Formation Shale in Well Ping’an 3, Sichuan Basin
- Ordered-to-disordered transfer learning with graph neural networks for formation-energy and HOMO-LUMO gap prediction in high-entropy perovskite oxides
BibTeX
@article{liao2026analysis,
title = {{Analysis of Enrichment-Controlling Factors and Seismic Prediction of Gas-Rich Zones in Tight Sandstone Gas Reservoirs: A Case Study from the Second Member of the Qianfoya Formation in Bazhong Area, Sichuan Basin}},
author = {Yuxuan Liao and Jineng Jin and Jinxiong Shi and Ce Wang and Shiqi Zhang and Wei Yan and Tao Wang},
journal = {ACS omega},
year = {2026},
month = oct,
doi = {10.1021/acsomega.6c07726},
url = {https://europepmc.org/article/PMC/PMC13670830},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Analysis of Enrichment-Controlling Factors and Seismic Prediction of Gas-Rich Zones in Tight Sandstone Gas Reservoirs: A Case Study from the Second Member of the Qianfoya Formation in Bazhong Area, Sichuan Basin
AU - Yuxuan Liao
AU - Jineng Jin
AU - Jinxiong Shi
AU - Ce Wang
AU - Shiqi Zhang
AU - Wei Yan
AU - Tao Wang
PY - 2026
DA - 2026/10/02
JO - ACS omega
DO - 10.1021/acsomega.6c07726
UR - https://europepmc.org/article/PMC/PMC13670830
AB - The Qianfoya Formation in the Bazhong area of the Sichuan Basin comprises a typical tight sandstone formation characterized by low porosity, low permeability, and strong reservoir heterogeneity. Effective reservoirs in this region are relatively thin, and seismic responses between gas-bearing layers and dry layers differ only slightly. These geological complexities create substantial challenges for predicting tight sandstone reservoirs and gas-rich zones, which necessitate targeted and effective geological and geophysical prediction research. Therefore, taking the Second Member of the Qianfoya Formation (Qian-2 Member) as the research object, this study utilizes multiwell logging, mud logging, and 3D seismic data sets. We first analyze the geological characteristics of the target interval to clarify the primary controlling factors of tight sandstone gas reservoir enrichment. Based on these factors, we establish an effective geophysical prediction workflow tailored for gas-bearing tight sandstone reservoirs. This method is further applied to predict gas-rich zones within the Qian-2 Member. The study concludes that (1) the main controlling factors for tight gas reservoir enrichment in the Qian-2 Member are sedimentary facies distribution, reservoir-cap rock conditions, and fracture distribution. (2) Prestack simultaneous inversion integrated with rock physics analysis enables effective sand-body identification. Rock physics analysis identifies P-wave impedance (Zp) and S-wave impedance (Zs) as the sensitive parameter pair for sand bodies. A sand-body factor prediction model is then constructed via coordinate rotation. Sensitive parameters are derived from prestack simultaneous inversion, and the sand-body factor is calculated from the prediction model. High positive values of the sand-body factor are used to predict sand-body distribution. (3) Based on near- and far-offset seismic comparison, the dominant amplitude–frequency method is used to extract the gas-bearing prediction attributes, whose positive anomalies effectively identify gas-bearing intervals. (4) A multifactor prediction framework combining sand bodies, gas-bearing properties, and fractures is adopted for gas-rich zones prediction. The results show that gas-rich zones in the Qian-2 Member are concentrated in the middle and upper submembers, and the predicted favorable zones are mainly distributed around faults. (5) This study establishes a workflow for predicting gas-rich zones of tight sandstone gas reservoirs via multifactor geological superposition analysis. Well-seismic calibration verifies its applicability, providing a methodological foundation and practical reference for the comprehensive prediction of favorable targets in similar tight sandstone gas reservoirs.
SN - 2470-1343
ER -