Basin Modeling in the Kuqa Depression of the Tarim Basin (Western China): A Fully Temperature-dependent Model of Overpressure History

摘要

Abstract The fully temperature-dependent model of the effective pressure of the solid matrix and its related overpressure has been derived from the pressure balance equation, mass conservation, and Darcy's law, and is directly useful in basin model-ing. Application of the model in the Kuqa Depression of the Tarim Basin in western China proves that this overpressure model is highly accurate. The case of the present-day values of the calculated overpressure histories of Wells Kela2 and Yinan2 ap-proach the field-measured data with mean absolute relative residuals of 3% and 5%, respectively. This indicates that the overpressure simulation is a practical alternative to using rock mechanics experiments for effective pressure measurement. Since cal-culation of the overpressure history uses the geohistory model and geothermal history model simulation outcomes, the relevant data used and the output of the two models of the Kela2 well are given as examples. The case studies show that the pore fluid density and viscosity used in the calcula-tion of overpressures should be temperature-dependent, otherwise the calculation re-sults would deviate far from the field-measured pressure data. They also show that the most sensitive parameter governing overpressure is permeability, and permeability can be calculated by using either the Kozeny—Carman formula or the porosity—power function. The Kozeny—Carman formula is better if accurate data for the specific surface area of the solid matrix (Se,) exists, otherwise, the porosity—power function is used. Furthermore, it is vital for calculating an accurate overpressure history that one can calibrate S, in the Kozeny—Carman formula, or index m in the porosity—power function by using field-measured pressure data as a constraint. In these specific case studies, the outcome found by using the Kozeny—Carman formula approaches the outcome found by using the porosity—power function with m 4, and both approach the field-measured pressure data.