Optimizing Refracturing Models in Tight Oil Reservoirs: An Integrated Workflow of Geology and Engineering Based on Seepage-Stress Real-Time Cross-Coupling Strategy

Summary Integrated modeling of refracturing is a comprehensive and complex task for engineers involved in field development, especially in previously developed mature fields. The modeling process requires consideration of numerous factors to accurately predict fracture propagation patterns during refracturing and production. During the initial fracturing process, hydraulic fractures generate an altered induced stress field. Later, during the post-fracturing production process, hydrocarbon extraction causes formation pore pressure depletion, leading to further alterations in the stress field. However, due to the complexity of these phenomena, most existing workflows simplify the coupled simulation problems of stresses at different stages in the modeling process. Consequently, this often results in questionable hydraulic fracture geometries during refracturing and suboptimal refracturing designs. The goal of this study is to develop a novel integrated workflow for refracturing, specifically tailored for complex fracture networks in tight oil reservoirs. This model incorporates the hydraulic fracture propagation process during the initial fracturing and dynamic stress changes during the initial production process. It employs artificial intelligence algorithms to calibrate the wellhead treating pressure using a physics-based model, enabling a better understanding of the initial fracturing fracture geometries. The production history match is then conducted based on the initially calibrated hydraulic fracture geometries, preserving the precision of the original fracture geometry. In addition, geomechanics modeling is conducted to obtain dynamic stress changes during the initial production process. For the refracturing design, the fracture propagation model for the refracturing process is later conducted on the depleted stress field. Following a 240-day period after refracturing, the production history is matched using an artificial intelligence–assisted reservoir simulator. Our results indicate that, due to prolonged production, significant changes occur in the stress field during the initial development period, with an average horizontal stress deviation angle of approximately 35° in the near-well zone. With the combined influence of the changing stress field and natural fractures, refracturing results in longer and more complex hydraulic fracture geometries, ultimately increasing individual well production.

Authors

Institutions

Publication Details

Journal
SPE Journal
Published
2024-08-29
DOI
https://doi.org/10.2118/223101-pa
Citations
6
Primary Topic
Hydraulic Fracturing and Reservoir Analysis
Type
article
Field-Weighted Citation Impact
1.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing Refracturing Models in Tight Oil Reservoirs: An Integrated Workflow of Geology and Engineering Based on Seepage-Stress Real-Time Cross-Coupling Strategy

Junbin Chen, Jiawei Ren, Xiaohu Bai, Wei Yu et al.
6 citations
SPE Journal
Hydraulic Fracturing and Reservoir Analysis
1.28
article

Optimizing Refracturing Models in Tight Oil Reservoirs: An Integrated Workflow of Geology and Engineering Based on Seepage-Stress Real-Time Cross-Coupling Strategy

Junbin Chen, Jiawei Ren, Xiaohu Bai, Wei Yu, Hongjun Lü
article en
6 citations

Abstract

Summary Integrated modeling of refracturing is a comprehensive and complex task for engineers involved in field development, especially in previously developed mature fields. The modeling process requires consideration of numerous factors to accurately predict fracture propagation patterns during refracturing and production. During the initial fracturing process, hydraulic fractures generate an altered induced stress field. Later, during the post-fracturing production process, hydrocarbon extraction causes formation pore pressure depletion, leading to further alterations in the stress field. However, due to the complexity of these phenomena, most existing workflows simplify the coupled simulation problems of stresses at different stages in the modeling process. Consequently, this often results in questionable hydraulic fracture geometries during refracturing and suboptimal refracturing designs. The goal of this study is to develop a novel integrated workflow for refracturing, specifically tailored for complex fracture networks in tight oil reservoirs. This model incorporates the hydraulic fracture propagation process during the initial fracturing and dynamic stress changes during the initial production process. It employs artificial intelligence algorithms to calibrate the wellhead treating pressure using a physics-based model, enabling a better understanding of the initial fracturing fracture geometries. The production history match is then conducted based on the initially calibrated hydraulic fracture geometries, preserving the precision of the original fracture geometry. In addition, geomechanics modeling is conducted to obtain dynamic stress changes during the initial production process. For the refracturing design, the fracture propagation model for the refracturing process is later conducted on the depleted stress field. Following a 240-day period after refracturing, the production history is matched using an artificial intelligence–assisted reservoir simulator. Our results indicate that, due to prolonged production, significant changes occur in the stress field during the initial development period, with an average horizontal stress deviation angle of approximately 35° in the near-well zone. With the combined influence of the changing stress field and natural fractures, refracturing results in longer and more complex hydraulic fracture geometries, ultimately increasing individual well production.

SPE JournalVol. 29(11)
Xi'an Shiyou University (CN), Simulation Technologies (United States) (US)
Openalex Percentile: Top 23%
Hydraulic Fracturing and Reservoir Analysis
1.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.