Exxonmobil Upstream Research Company

Shiyu Xu

Rebecca L Saltzer

Enru Liu

Ganglin Chen

Michael A Payne

Limin Song

Max Deffenbaugh

Xinyou Lu

Robert G Keys

John Henry Dunsmuir

Christopher J Finn

Michael E Farrell

Yaping Zhu

Carrie X Zhan

Carrie Xin Zhan

A hydrocarbon exploration method is disclosed for developing a model of at least one effective material property of a subsurface reservoir as a function of the composition and structure of the reservoir rock. In one embodiment, the method comprises: obtaining a 3D image () of a rock sample characteristic of a reservoir of interest (); segmenting the 3D image into compositional classes () based on similarities in mineralogy, structure and spatial distribution; selecting a model () that relates an effective material property of interest to the volume fractions of each compositional class; and determining the parameters of the model (). The model may be used to assess the commercial potential of the subsurface reservoir ().

Method for determining the properties of hydrocarbon reservoirs from geophysical data

A hydrocarbon exploration method is disclosed for generating anisotropic resistivity models of a subsurface reservoir from seismic and well data using a rock physics model. In one embodiment, the method comprises: selecting wells within a region of interest (); obtaining a plurality of rock properties () and adjusting selected rock parameters () in the calibration of the rock physics model at the well locations; inverting porosity and shale content from seismic data (); propagating the calibrated rock physics model to the region of interest () and calculating effective resistivity for the entire region of interest (). The inventive method also provides for analyzing the uncertainty associated with the prediction of the resistivity volume.

Method for generating anisotropic resistivity volumes from seismic and log data using a rock physics model

Method for modeling anisotropic elastic properties of a subsurface region comprising mixed fractured rocks and other geological bodies. P-wave and fast and slow S-wave logs are obtained, and an anisotropic rock physics model of the subsurface region is developed (). P- and fast and slow S-wave logs at the well direction are calculated using a rock physics model capable of handling fractures and other geological factors (). Calculated values are compared to measured values in an iterative model updating process (). An upscaled ID model is developed by averaging elastic properties in each layer using an upscaling theory capable of handling at least orthorhombic anisotropy (). The ID model may be used to generate synthetic seismic response for well ties or AVO modeling (). Further, a method is disclosed for estimating anisotropy parameters from P- and fast/slow S-wave logs from one or more deviated wells.

Rock physics model for simulating seismic response in layered fractured rocks

Method for constructing an integrated rock physics model that simulates both shale anisotropy and stress-induced anisotropy of clastic rocks. In the model, the total pore volume is divided into three parts according to the estimated shale volume and effective stress: (1) clay-related pores, (2) sand-related pores, and (3) microcracks (mainly in the sand component). The pore space is then partitioned into the clay-related and sand-related pores using a scheme first disclosed by Xu and White in 1995. The model simulates shale anisotropy via the preferred orientation of clay-related pores and stress-induced anisotropy via the preferred orientation of microcracks, which is controlled by the differential stresses. Laboratory measurements or well logs are needed to establish a relationship between crack density and the effective stress.

Integrated anisotropic rock physics model

Method for predicting lithology and porosity of subsurface rocks from seismic reflection data. The seismic data is inverted to yield elastic properties of the rocks such as the compressional and shear impedances. A rock physics model is built to relate porosity, the shale volume fraction, the fluid content of the rock and the elastic properties of the rock. The model is run backward in a second inversion process to solve for porosity and lithologic properties such as the shale volume fraction.

Method for predicting lithology and porosity from seismic reflection data

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Kingwood, TX, United States of America

Shiyu Xu