A New Post-Drilling Evaluation Method for Formation Pore Pressure

Abstract

ABSTRACT Eaton and Bowers model are two commonly used methods for formation pore pressure evaluation methods. However, both of them belong to univariate model, which takes few factors into consideration, is subject to many conditions, and has large error. Therefore, combining the results of previous laboratory experiments and field logging data, the correlation between shale content, density, porosity, effective stress and p-wave velocity was analyzed. The function form of each factor term was optimized, and a new p-wave velocity model was established by using multivariate nonlinear regression. Based on the effective stress theorem, a new post-drilling evaluation method for formation pore pressure was proposed. The results show that the density, porosity and effective stress are highly correlated with the p-wave velocity, while the shale content is relatively low. The optimal function forms of their correlation with p-wave velocity are linear, "linear + exponential" combination form, power function form, and linear form, respectively. The accuracy of the developed model is more than 99%, which is much higher than the Eaton and Bowers model. The research results have important reference significance for improving the evaluation accuracy of formation pore pressure, and provide a basis for rational casing design, determination of mud density and adjustment of production technology. INRTUDUCTION Formation pore pressure refers to the fluid pressure in the pores of formation. The establishment of a reasonable pore pressure profile is the basis for the reasonable casing design, the mud density determination and the production technology adjustment (Fan, 2006). The logging information can reflect the compaction law of formation and the lithology and physical property of underground rock, and the data amount is very large, which is the most ideal data for evaluating pore pressure. Therefore, using logging data to evaluate pore pressure after drilling is the one of most effective methods (Wang and Guo, 2015). At present, almost all formation pore pressure evaluation methods are indirect estimation based on p-wave velocity, resistivity, density, porosity and other logging parameters as well as effective stress. The evaluation methods mainly fall into two categories: one is based on the normal compaction trend line (Foster, 1966; Ham, 1966; Eaton, 1972, 1975); the other is based on the effective stress theorem (Bellotti, 1978; Bowers, 1995, 2001; Bryant 1989; Alixant, 1991). The above models are univariate models with few factors, more constraints and large errors.