Abstract

ABSTRACT Prediction methods for the pore pressure of clastic rock formation are almost mature worldwide. However, due to the characteristics of carbonate rock formation, such as high matrix rigidity, pronounced heterogeneity, and the uncertain formation mechanism of abnormal pressure, the traditional prediction methods of formation pore pressure are difficult to apply in carbonate formation, which seriously threatens the drilling safety. Therefore, the method for calculating the pore pressure of carbonate formation was studied. Taking the carbonate formation of the Majiagou Group in the Mid-Eastern Ordos Basin as an example, this paper put forward a comprehensive interpretation of various logging parameters related to the formation mechanism of abnormal pressure. It established a pore pressure prediction model applicable to carbonate formation, which is not limited to the under-compaction theory using multiple nonlinear regression methods. The formation pore pressure detection method was applied to multiple wells in the Majiagou Group, Mid-Eastern Ordos Basin. The application results showed that the relative error of formation pore pressure between the model detection and measured values was less than 10%, which satisfy engineering requirements. It also provides a new approach to address the problem of pore pressure detection of carbonate formation. INTRODUCTION Abnormal high pressure has an important impact on the development of conventional and unconventional oil and gas reservoirs, which may cause many complex accidents, such as wellbore instability, drilling fluid leakage, and blowout. With the development of oil and gas reservoirs towards the complex formation, formation pore pressure prediction plays an increasingly important role in the future development of oil and gas reservoirs. Reasonable and accurate prediction of formation pore pressure is the basis for the rational design of drilling fluid density, wellbore structure design, and wellbore pressure maintenance. It also guarantees safe, effective, and rapid drilling. Formation pore pressure prediction includes forward-looking pre-drilling prediction, timely monitoring while drilling, and reference post-drilling detection. Among them, the accuracy of post-drilling detection is the highest. The logging data of adjacent and exploratory wells can provide theoretical support and reference for target wells’ formation pore pressure prediction.

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