考虑深度和声波偏量的密度拟合对地层压力预测精度的影响

Influence of the density fitting considering depth and acoustic deviator on the formation pressure prediction precision

赵毅 李忠慧 赵林 方满宗 吴惠梅

ZHAO Yi LI Zhonghui ZHAO Lin FANG Manzong WU Huimei

长江大学石油工程学院 油气钻井技术国家工程实验室防漏堵漏研究室 中国石化河南油田分公司石油工程技术研究院 中海油能源发展股份有限公司工程技术湛江分公司

Petroleum Engineering College, Yangtze University, Wuhan 430100, Hubei, China Lost Circulation Prevention and Control Laboratory, National Engineering Laboratory for Oil and Gas Drilling Technology, Wuhan 430100, Hubei, China Research Institute of Petroleum Engineering，SINOPEC He’nan Oilfield Company, Nanyang 473000, He’nan, China Zhanjiang Branch, CNOOC EnerTech-Drilling & Production Co., Zhanjiang 524057, Guangdong, China

随着深水钻井技术的不断发展，窄密度窗口钻井愈发常见，深水地层压力预测精度要求随之增加。深水地层密度拟合是上覆岩层压力预测及地层压力分析不可或缺的基础，单一模型不能准确预测深水地层上覆岩层压力。鉴于此，对比伊顿指数法的孔隙压力预测过程，以非线性拟合为基础，在Power Law模型的基础上引入声波偏量对密度的影响，分析声波偏量与密度的非线性关系，提出一种修正的密度拟合模型。模型在理论上综合考虑地层正常压实情况及声波速度变化反映的密度异常，更符合实际，解决了单一模型无法准确拟合深水地层密度的难题，破裂压力预测误差由6.36%降低至2.73%。

With the continuous development of deepwater drilling technologies, the drilling of narrow-density window tends to happen more frequently, and correspondingly the pressure prediction precision of deepwater formation is required more strictly. The density fitting of deepwater formation is the indispensable foundation for predicting the overlying rock pressure and analyzing formation pressure. Based on existing single model, however, the overlying rock pressure of deepwater formation cannot be predicted accurately. In this paper, referring to the pore pressure prediction process of the Eaton method of index number, combined with the non-linear fitting, the effect of acoustic deviator on the density was introduced into the Power-Law model to analyze the non-linear relationship between acoustic deviator and density. Then, a kind of corrected density fitting model was put forward. This model theoretically takes comprehensive consideration of the normal formation compaction and the abnormal density reflected by the change of acoustic velocity, so it can reflect the actual situations more accurately. In addition, it solves the difficulty that one single model cannot provide accurate density fitting of deepwater formation, and the prediction error of the fracturing pressure is reduced from 6.36% to 2.73%.

10.13639/j.odpt.2020.01.005