基于人工神经网络优化算法的油气水三相相平衡计算

doi:10.3799/dqkx.2026.013

基于人工神经网络优化算法的油气水三相相平衡计算

doi: 10.3799/dqkx.2026.013

1. 东北石油大学多资源协同陆相页岩油绿色开采全国重点实验室，黑龙江大庆 163318
2. 大庆油田有限责任公司第二采油厂，黑龙江大庆 163000

基金项目:

黑龙江省自然科学基金优秀青年项目(YQ2024E008)

详细信息

作者简介:
沈安琪，女，1986年3月生，2017年获东北石油大学博士学位，现为东北石油大学副教授、博士生导师，主要从事渗流、提高油气采收率、流体相态等方面研究工作。Email：anqi1986@126.com，ORCID：https://orcid.org/0000-0002-8171-7120

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出版历程
- 收稿日期: 2025-09-28
- 网络出版日期: 2026-01-28

A three-phase phase equilibrium calculation for oil, gas and water based on Artificial Neural Network and optimization algorithm

摘要

摘要: 油气藏中的流体相态是评估储量、制定开发方案的基础；相平衡计算可提供多组分流体在不同环境下相态预测，为油气藏开发提供关键基础流体物性参数。本文基于传统热力学模型建立考虑CO₂溶于水的油气水三相相平衡计算模型。通过该模型获取数据样本，结合遗传算法（GA）和模拟退火算法（SA），基于人工神经网络建立油水气（含CO₂）三相相态预测模型，可计算相分率及各组分在油气水三相间摩尔分数。研究结果表明，基于人工神经网络优化算法的油气水三相相平衡预测模型误差在5%以内，其中GA、SA算法协同优化后的模型准确率最高。将传统热力学计算与神经网络遗传、模拟退火优化算法相结合，可为复杂的三相相平衡计算提供指导。
- 相平衡计算 /
- 遗传优化算法 /
- 模拟退火优化算法 /
- 亨利定律
Abstract: The fluid phase state in oil and gas reservoirs is the basis for evaluating reserves and development plans; phase equilibrium calculations can provide phase state predictions of multi-component fluids under different conditions, providing basic fluid physical parameters for oil and gas reservoir. Due to the solubility of CO₂ in water, to study the phase fraction and component variation characteristics of the coexisting oil-water-gas (including CO₂) system, a three-phase phase equilibrium calculation model for oil-water-gas (including CO₂) is established based on the traditional thermodynamic model, considering the solubility of CO₂ in water. Data obtained through this model are used to form a sample set, and combined with genetic algorithm (GA) and simulated annealing algorithm (SA), an artificial neural network-based three-phase phase state prediction model for oil-water-gas (including CO₂) is established, obtaining the phase fraction and mole fraction of each component in the oil-water-gas three phases. The research results show that the error of the three-phase phase equilibrium prediction model based on the artificial neural network optimization algorithm is controlled within 5%, among which the model optimized by GASA together has the highest accuracy. The combination of traditional thermodynamic calculation and neural network genetic and simulated annealing optimization algorithms can provide guidance for complex three-phase phase equilibrium calculations.
- Phase equilibrium calculation /
- Genetic algorithm /
- Simulated annealing algorithm /
- Henry's law

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基于人工神经网络优化算法的油气水三相相平衡计算

doi: 10.3799/dqkx.2026.013

作者简介:
沈安琪，女，1986年3月生，2017年获东北石油大学博士学位，现为东北石油大学副教授、博士生导师，主要从事渗流、提高油气采收率、流体相态等方面研究工作。Email：anqi1986@126.com，ORCID：https://orcid.org/0000-0002-8171-7120

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A three-phase phase equilibrium calculation for oil, gas and water based on Artificial Neural Network and optimization algorithm

计量

目录

留言板

基于人工神经网络优化算法的油气水三相相平衡计算

doi: 10.3799/dqkx.2026.013

作者简介: 沈安琪，女，1986年3月生，2017年获东北石油大学博士学位，现为东北石油大学副教授、博士生导师，主要从事渗流、提高油气采收率、流体相态等方面研究工作。Email：anqi1986@126.com，ORCID：https://orcid.org/0000-0002-8171-7120

计量

出版历程

A three-phase phase equilibrium calculation for oil, gas and water based on Artificial Neural Network and optimization algorithm

计量

出版历程

目录

作者简介:
沈安琪，女，1986年3月生，2017年获东北石油大学博士学位，现为东北石油大学副教授、博士生导师，主要从事渗流、提高油气采收率、流体相态等方面研究工作。Email：anqi1986@126.com，ORCID：https://orcid.org/0000-0002-8171-7120