Exxonmobil Upstream Research Company

Enru Liu

Limin Song

Robert J Pottorf

Peng Xu

Shiyu Xu

Yaping Zhu

Gordon Macleod

Michael A Payne

Dennis Patrick Smith

Max Deffenbaugh

Matthias Imhof

Christine E Krohn

Xinyou Lu

Dominique Gillard

Matthew S Casey

Ganglin Chen

John Henry Dunsmuir

John H Dunsmuir

John E Mayhew

Fuping Zhou

Xiaoxia Xu

Julianna J Toms

Carrie X Zhan

Kaushik Bandyopadhyay

J Clayton Bell

Carrie Xin Zhan

Dennis Smith

Accordingly, there are disclosed herein geologic modeling methods and systems employing reference-based inversion of seismic image volumes. An illustrative method embodiment includes: (a) obtaining a measured seismic image volume; (b) determining a reference seismic image volume based on a reference model; (c) deriving a synthesized seismic image volume from a geologic model; (d) detecting at least one geologic model region where the synthesized seismic image volume and the measured seismic image volume are mismatched; (e) finding a reference model region where the reference seismic image volume best matches the measured seismic image volume; (f) replacing content of the at least one geologic model region with content of the reference model region to obtain an improved geologic model; and (g) outputting the improved geologic model.

Methods and systems for reference-based inversion of seismic image volumes

A system and method to predict rock strength by directly inverting for petrophysical properties. In one embodiment, seismic data is received or obtained from a seismic survey (step). The seismic data are then conditioned (step) in order to prepare them for an inversion process (step). The inversion process has an embedded rock physics model that allows the inversion to be formulated based upon, and thereby outputting or calculating (step), petrophysical properties. Rock strength data may then be calculated from the petrophysical properties (step).

Method for predicting rock strength by inverting petrophysical properties

Systems and methods which determine geologic properties using acoustic analysis are shown. Acoustic signals are collected during processing (e.g., crushing, shearing, striking, compressing, etc.) of geologic media, such as rock samples, for determining geologic properties according to embodiments. The acoustic signals collected may include frequency information, amplitude information, time information, etc. which may be utilized in determining geologic properties, such as geologic media properties (e.g., mineralogy, porosity, permeability, sealing capacity, fracability, compressive strength, compressibility, Poisson's Ratio, Youngs Modulus, Bulk Modulus, Shear Modulus), geologic structure properties (e.g., lithology, seal quality, reservoir quality), geologic acoustic properties (e.g., acoustic logging effectiveness, acoustic response, natural or harmonic frequencies, etc.). Embodiments may be used to provide determination of geologic properties from a variety of geologic media samples, such as cuttings, core samples, etc.

Systems and methods for determining geologic properties using acoustic analysis

Method for estimating fluid heterogeneity in a subsurface region from seismic wave attenuation or velocity dispersion that is either measured or extracted from geophysical data (). A rock physics model in the form of a mathematical relationship is selected that relates attenuation or velocity to frequency and to physical properties that are related to fluid heterogeneity (). The model, or asymptotes () representing the model's behavior at frequency extremes, is inverted () and that relationship is used to obtain () one or more of the physical properties related to fluid heterogeneity, such as characteristic length scale for fluid saturation heterogeneities () and relative volume fractions of the fluids saturating the pore space ().

Estimation of production sweep efficiency utilizing geophysical data

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

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Sugar Land, TX, United States of America

Enru Liu