Chevron U.s.a. Inc.

Cory James Hoelting

Maisha Lara Amaru

Philip Stephan Schultz

Chaoshun Hu

Andrey H Shabelansky

Huafeng Liu

Weihong Fei

Gilles Hennenfent

Jinsong Chen

Ying Tan

Min Yang

Paige Rene Given

Systems and methods for estimating reservoir productivity as a function of position in a subsurface volume of interest are disclosed. Exemplary implementations may: obtain an initial depth uncertainty model; obtain training depth uncertainty parameter values from the non-transient storage medium; obtain corresponding training depth uncertainty values; generate a trained depth uncertainty model by training the initial depth uncertainty model using the training depth uncertainty parameter values and the corresponding training depth uncertainty values; and store the trained depth uncertainty model.

Systems and methods for generating depth uncertainty values as a function of position in a subsurface volume of interest

A method is described for seismic depth uncertainty analysis including receiving wavelet basis functions and cutoff thresholds and randomly perturbing wavelet coefficients in reduced wavelet space based on the wavelet basis functions and the cutoff thresholds to generate a plurality of random wavelet fields; receiving a reference model in a depth domain; transforming the plurality of random wavelet fields to the depth domain and combining them with the reference model to form candidate models; performing a hierarchical Bayesian modeling with Markov Chain Monte Carlo (MCMC) sampling methods using the candidate models as input to generate a plurality of realizations; and computing statistics of the plurality of realizations to estimate depth uncertainty. The method may be executed by a computer system.

System and method for seismic depth uncertainty analysis

Embodiments of a method for correcting velocity models for complex topographies are disclosed herein. In general, embodiments of the method utilize velocity corrections based on geomechanical effects to correct a velocity model to take into account complex surface topographies. In particular, embodiments of the method use a nucleus strain theory to determine the velocity corrections. Further details and advantages of various embodiments of the method are described in more detail herein.

Method of correcting velocity for complex surface topography

A system and method for subsurface characterization including depth and structural uncertainty estimation is disclosed. In one embodiment, the method may include determining a detectability threshold for moveout in a seismic data gather based on the seismic data and computing a depth uncertainty function, wherein the depth uncertainty function represents an error estimate that is used to analyze an interpretation of the seismic data. In another embodiment, the method may include receiving a depth uncertainty volume and at least one interpreted horizon from seismic data, extracting a depth uncertainty cage for each of the interpreted horizons based on the depth uncertainty volume, and simulating multiple realizations for each of the interpreted horizons, constrained by the depth uncertainty cage. The multiple realizations may be used for analyzing changes to geometrical or structural properties of the at least one interpreted horizon. The changes may be plotted as at least one distribution and may be used to make P10, P50 and P90 estimates.

System and method for subsurface characterization including uncertainty estimation

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Houston, TX, United States of America

Cory James Hoelting