A Novel Method for Fracture Pressure Prediction in Shallow Formation During Deep-Water Drilling

Author:

Yang Jin1,Liu Shujie2,Wang Huanhuan1,Zhou Xu3,Song Yu1,Xie Renjun4,Zhang Zhenxiang1,Yin Qishuai1,Xu Fei1

Affiliation:

1. College of Safety and Ocean Engineering, China University of Petroleum-Beijing, Beijing 102249, China

2. CNOOC China Limited, Zhanjiang Branch, Zhanjiang 524057, China

3. Louisiana State University, Baton Rouge, LA 70803

4. CNOOC Research Institute Co., Ltd Beijing 100028, China

Abstract

Abstract Large numbers of deep-water drilling practices have shown that more than 60% of deep-water wells have complex leak-off during the drilling process, which poses great difficulties and challenges for the safety and operation time of deep-water drilling. The purpose of this article is to establish a method for predicting the fracture pressure in shallow formations. In this study, the deep-water shallow formation was divided into the upper unconsolidated soil layer, and the lower diagenetic rock layer according to the geotechnical distribution characteristics of the deep-water shallow formation. The location of the transition soil/rock layer zone was determined using the upper soil layer density trend line, and the lower rock layer density log data regression trend line. The deep-water shallow fracture pressure prediction model was established based on the soil/rock transition zone. The shear failure criterion was used above the transition zone, and the tensile failure criterion is used below the transition zone. The shallow fracture pressure of six drilled exploratory wells in the X block from the South China Sea was calculated using this new method and the calculation errors were all less than 3.18%. Moreover, the shallow fracture pressure body in this block was established using the Kriging interpolation method based on six drilled exploratory wells data. This shallow fracture pressure body established here was used to predict nine development wells shallow fracture pressure with a predictive error of less than 1.7% and there were no drilling accidents. The case study demonstrates that the new model can significantly improve the prediction accuracy has good prospects for popularization and application.

Funder

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Publisher

ASME International

Subject

Geochemistry and Petrology,Mechanical Engineering,Energy Engineering and Power Technology,Fuel Technology,Renewable Energy, Sustainability and the Environment

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