Research on Multi-Objective Optimization and Smart Proration Model for Gas Reservoirs Based on Integrated Systems

Abstract In response to the series of issues in gas field development such as underutilization of pipeline transport capacity, low ultimate recovery factor, and mismatch between gas extraction and end-user supply leading to irrational well proration, this paper proposes a multi-objective and multi-constraint optimization approach for proration based on an integrated system. Initially, the reservoir, wellbore, and pipeline network are coupled to form an integrated production simulation system. Reservoir simulation is conducted to obtain bottom-hole pressure and gas-liquid flow data for individual wells, while wellbore simulation provides pressure and flow rates at the wellhead nodes, which serve as the basis for pipeline network simulation. Subsequently, with the proration of individual wells as the basic variable and constraints defined by the reservoir, single well, pipeline transport, production equipment conditions, and production targets, the optimization seeks to maximize gas output and minimize water production. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) with an elitist strategy is used to find the optimal proration scheme. This method takes into account both the production capacity of gas wells and the characteristics of the gathering and transportation pipeline network to ensure short-term supply and emergency proration needs, as well as the equipment requirements of each segment of the production system and reservoir characteristics to ensure optimal long-term development throughout the reservoir’s life cycle. Applying this method to the domestic BZ gas field for proration and forecasting, with the ultimate goal of maximizing gas production and minimizing water output, and incorporating constraints on single well liquid loading and erosion rates, the cumulative gas production for 2 zones and 7 wells was simulated. Compared to manual proration schemes, the final gas production increased by 4%, while achieving a stable production period of approximately 5 years, thus maximizing downstream gas supply requirements.

Authors

Institutions

Publication Details

Journal
Journal of Physics Conference Series
Published
2025-09-01
DOI
https://doi.org/10.1088/1742-6596/3048/1/012026
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Multi-Objective Optimization and Smart Proration Model for Gas Reservoirs Based on Integrated Systems

Lei Xu, Qiantiao Xie, Wei Qian, Ying Zhao et al.
Journal of Physics Conference Series
Reservoir Engineering and Simulation Methods
article

Research on Multi-Objective Optimization and Smart Proration Model for Gas Reservoirs Based on Integrated Systems

Lei Xu, Qiantiao Xie, Wei Qian, Ying Zhao, Hong Xu, Jing Gong, Hao-yu Shi
article en

Abstract

Abstract In response to the series of issues in gas field development such as underutilization of pipeline transport capacity, low ultimate recovery factor, and mismatch between gas extraction and end-user supply leading to irrational well proration, this paper proposes a multi-objective and multi-constraint optimization approach for proration based on an integrated system. Initially, the reservoir, wellbore, and pipeline network are coupled to form an integrated production simulation system. Reservoir simulation is conducted to obtain bottom-hole pressure and gas-liquid flow data for individual wells, while wellbore simulation provides pressure and flow rates at the wellhead nodes, which serve as the basis for pipeline network simulation. Subsequently, with the proration of individual wells as the basic variable and constraints defined by the reservoir, single well, pipeline transport, production equipment conditions, and production targets, the optimization seeks to maximize gas output and minimize water production. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) with an elitist strategy is used to find the optimal proration scheme. This method takes into account both the production capacity of gas wells and the characteristics of the gathering and transportation pipeline network to ensure short-term supply and emergency proration needs, as well as the equipment requirements of each segment of the production system and reservoir characteristics to ensure optimal long-term development throughout the reservoir’s life cycle. Applying this method to the domestic BZ gas field for proration and forecasting, with the ultimate goal of maximizing gas production and minimizing water output, and incorporating constraints on single well liquid loading and erosion rates, the cumulative gas production for 2 zones and 7 wells was simulated. Compared to manual proration schemes, the final gas production increased by 4%, while achieving a stable production period of approximately 5 years, thus maximizing downstream gas supply requirements.

Journal of Physics Conference SeriesVol. 3048(1)
China University of Petroleum, Beijing (CN), Beijing Academy of Artificial Intelligence (CN), Daqing Oilfield General Hospital (CN), China National Petroleum Corporation (China) (CN)
Openalex Percentile: Top 70%
Reservoir Engineering and Simulation Methods
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.