Prediction Model of Rock Mechanics Parameters in Ultra-DeepFractured Formations Based on Big Data
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摘要:
超深储层油气资源丰富，是目前油气开发的重点，但是储层岩体破碎和非均质性强，传统的预测储层力学参数方法误差大，对工程设计和施工造成很大的困难。基于大量试验和现场施工数据，分析了储层测井数据、储层裂缝数据、岩石力学数据的相互联系，建立了基于岩石力学性质−地质储层特征−测井解释之间物理关联的多参数约束；开发了多元非线性回归拟合算法模型，形成了超深破碎型储层全储层段岩石力学参数预测模型。该预测模型克服了破碎型地层数据量少导致的计算误差大的难题，能明确全储层段岩石力学参数，与实际工程施工参数相比预测准确度达90%以上。研究结果为超深破碎型地层钻完井安全施工提供了技术支撑。
Abstract:The rich oil and gas resources in ultra-deep reservoirs are the focus of oil and gas development at present. However, due to the high fragmentation and strong heterogeneity of rock mass in reservoirs, the traditional method of predicting reservoir mechanics parameters has a large error, which causes great difficulties in engineering design and operation. Based on a large number of experimental and field operation data, the interrelationship among reservoir logging data, reservoir fracture data, and rock mechanics data was analyzed. A multi-parameter constraint was established based on the physical correlation between rock mechanical properties, geological reservoir characteristics and logging interpretation, and a multivariate nonlinear regression fitting model was developed to predict rock mechanics parameters in the whole reservoir section of ultra-deep fractured reservoirs. The prediction model overcame the problem of large calculation errors caused by small amount of fractured formation data and could determine the rock mechanics parameters in the whole reservoir section. Compared with the actual operation parameters, the prediction accuracy is more than 90%. The research results provide technical support for the safe operation of drilling and completion in ultra-deep fractured formations.
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图 6 X1井储层段岩石力学参数预测结果
Figure 6. Prediction results of rock mechanics parameters in reservoir section of Well X1
表 1 模型评估结果
Table 1 Model evaluation results
参数 均方差 平均绝对误差 决定系数 抗压强度 2.22 0.88 0.94 弹性模量 1.29 1.21 0.96 泊松比 2.50 2.42 0.89 
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