A rock physics model for characterizing the total porosity and velocity of shale: A case study in Fuling area, China. (January 2019)

• Record Type: Journal Article
• Authors: Xu, Zhuang; Shi, Wanzhong; Zhai, Gangyi; Clay, Campbell; Zhang, Xiaoming; Peng, Nyujia
• Is Part Of: Marine and petroleum geology. Volume 99(2019)
• Page Start: 208
• Page End: 226
• Publication Date: 2019-01
• Subjects: hale gas -- Fuling area -- Total porosity -- Artificial cores -- Rock physics; Submarine geology -- Periodicals; Petroleum -- Geology -- Periodicals; Géologie sous-marine -- Périodiques; Pétrole -- Géologie -- Périodiques; Petroleum -- Geology; Submarine geology; Periodicals; Electronic journals; 551.468
• DOI: 10.1016/j.marpetgeo.2018.10.010
• Languages: English
• ISSNs: 0264-8172

Abstract

Abstract: The total porosity in a shale gas reservoir is the key parameter to evaluate its potential production capability. Petroleum geologists have been pursuing an accurate way of predicting total porosity in shale gas reservoirs from logging curves. In the Fuling area near Chongqing in China, we use core test data and well logging data, in order to establish a logging response model for porosity. Through the analysis of the data, we found that the porosity and the P-sonic (P-velocity) have a strong correlation. By combining our results with previous research (i.e., physical rock data), we establish a new model which better predicts the total porosity of a given a shale reservoir than the models established in previous research. In addition to total porosity, mineral composition, pore pressure, pore fluid-type, and confining pressure affect P-velocity. By taking a series of artificial cores as test objects and systematic analysis of total porosity, mineral composition and content, pore fluid-type and pressure on the P-velocity, we establish response templates between every individual parameter and P-velocity. To this end, we further establish a multi-parameter rock physical characterization equation for the total porosity and P-velocity, and analyze its applicable conditions. Using the rich geological and geophysical data of the Lower Silurian Series in the Fuling area, we gradually improve the model for the total porosity and verify the results using well logging data. Finally, a set of accurate methods are established to predict the total porosity in shale gas reservoirs by using well logging data. Highlights: Eetermine the rock physical response parameters of quantitative characterization of total porosity. Establish the velocity prediction equation influence by individual parameter. Establish the characterization equation of total porosity in the Fuling area and test the accuracy of the equation.