A S-wave Velocity Prediction Method Based on Statistical Rock Physics Model

Abstract

The invention relates to a transverse wave velocity prediction method based on a statistical rock physical model, and belongs to the field of shale oil and gas resource exploration. According to the method, a Xu-White model is used to establish a relation between a rock internal property and an external velocity measurement value; in combination with prior information, the statistical rock physical model is built; then a Bayesian method is used for inverting intermediate parameters according to a measured longitudinal wave velocity in a well and other rock physical parameters; and finally, a transverse wave velocity is calculated, so that the purpose of predicating the transverse wave velocity in the well is achieved. According to the method disclosed by the invention, the defects in the prior art are overcome; a changed sandstone modulus and a changed pore aspect ratio are used; a Xu-White model-based transverse wave velocity prediction method is improved; a statistics theory is added; and the accuracy of the calculated transverse wave velocity in the well is higher. The method helps to improve the accuracy of reservoir evaluation in oil-gas resource exploration.

Description

technical field [0001] The invention relates to a shear wave velocity prediction method based on a statistical rock physics model, which belongs to the field of shale oil and gas resource exploration. Background technique [0002] Accurate shear wave velocity is an important constraint parameter for pre-stack seismic attribute analysis and inversion, and can be used for oil and gas reservoir lithology, attribute, potential evaluation, etc. However, due to the high cost of shear wave logging and the difficulty of interpretation, shear wave velocity has not been measured for all wells in actual production, and some old wells do not have shear wave velocity logging data. Existing technology can estimate the shear wave velocity by using parameters such as the longitudinal wave velocity measured in the well. Two methods are commonly used. One is to use empirical formulas to establish the relationship between parameters such as velocity and porosity, such as the linear empirical...

AI Technical Summary

Problems solved by technology

But for practical problems, the composition information of the sandstone in the well changes, and the modulus will change accordingly, and the change of the modulus will have a great impact on the velocity of the rock

Previous studies have ignored the effect of sandstone modulus changes

In addition, the existing data and research results in the same work area can be added to the calculation framework as prior information to improve the accuracy of shear wave velocity prediction in wells, but they have not been used to solve this problem

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