岩石力学参数标定系统关键技术研究

Key technology development on the calibration system of rock mechanics parameters

岩石力学参数建模在地应力建模、甜点预测与井网部署优化等研究工作中起着重要作用。利用常规测井资料计算井点岩石力学参数,并结合地质统计插值建立全区域三维岩石力学参数模型是最为常用的方法之一,但是该方法在一定程度上忽略了测井曲线之间的相关性与约束性。实际上,在很多油气勘探区块,岩石力学非均质性强,利用统计学方法建模会产生较大误差。针对以上问题,本文研发了岩石力学参数标定系统,提出利用与岩石力学参数相关性较强的声波时差、自然伽马参数等测井曲线约束初始岩石力学参数模型,从而克服以上缺陷,提高建模精度,并利用数据分块算法顺利实现了对亿级数量网格单元的岩石力学参数模型标定计算。

The rock mechanics parameter modeling plays an important role in the researches of in situ stress modeling, sweet-spot prediction and well-network optimization. One of the most used methods, i. e. , using conventional logging data to calculate the rock mechanical parameters combined with interpolation of geological statistics to establish the 3D model of rock mechanical parameters, ignores, to some extent, correlation and constraints between logging curves. In fact, heterogeneity of rock mechanics is strongly present in many oil gas prospecting fields, producing large errors in parameter modeling by statistical approach. To overcome this problem, this paper developed the rock mechanics parameter calibration system and proposed a way of using sonic and natural gamma logging parameters, which have strong correlation among mechanics parameters to constrain the initial model of rock mechanics parameters and thus improve modeling accuracy. Data block algorithm is also used to realize the mechanics modeling calibration successfully at the one hundred million grids level.