Exxonmobil Upstream Research Company

Exxonmobil Technology and Engineering Company

Ratnanabha Sain

Jan Schmedes

David D McAdow

Brent D Wheelock

Di Yang

Prajnajyoti Mazumdar

Amit Kushwaha

Yunfei Yang

Stan Lee

A method and system for modeling a subsurface region include applying a trained machine learning network to an initial petrophysical parameter estimate to predict a geologic prior model; and performing a petrophysical inversion with the geologic prior model, geophysical data, and geophysical parameters to generate a rock type probability model and an updated petrophysical parameter estimate. Embodiments include managing hydrocarbons with the rock type probability model. Embodiments include checking for convergence of the updated petrophysical parameter estimate; and iteratively: applying the trained machine learning network to the updated petrophysical parameter estimate of a preceding iteration to predict an updated rock type probability model and another geologic prior model; performing a petrophysical inversion with the updated geologic prior model, geophysical seismic data, and geophysical elastic parameters to generate another rock type probability model and another updated petrophysical parameter estimate; and checking for convergence of the updated petrophysical parameter estimate.

Petrophysical inversion with machine learning-based geologic priors

A method and apparatus for generating a fluid saturation model for a subsurface region. One example method generally includes obtaining a model of the subsurface region; for each of a plurality of fluid types: flooding the subsurface region model with the fluid type to generate a flood model; and running a trial petrophysical inversion with the flood model to generate a trial petrophysical model; identifying potential fluid contact regions in the trial petrophysical models; partitioning the subsurface region model at the identified potential fluid contact regions; and constructing the fluid saturation model from the partitioned subsurface region model.

Fluid saturation model for petrophysical inversion

A method and apparatus for generating an image of a subsurface region including obtaining geophysical data/properties for the subsurface region; resampling the geophysical data/properties to generate a resampled data set; iteratively (a) inverting the resampled data set with an initial prior model to generate a new model; and (b) updating the new model based on learned information to generate an updated prior model; substituting the initial prior model in each iteration with the updated prior model from an immediately-preceding iteration; and determining an end point for the iteration. A final updated model may thereby be obtained, which may be used in managing hydrocarbons. Inversion may be based upon linear physics for the first one or more iterations, while subsequent iterations may be based upon non-linear physics.

Reservoir characterization utilizing ReSampled seismic data

A method including: obtaining geophysical data for a subsurface region; generating, with a computer, at least two subsurface property models of the subsurface region for at least two subsurface properties by performing an inversion that minimizes a misfit between the geophysical data and forward simulated data subject to one or more constraints, the inversion including generating updates to the at least two subsurface property models for at least two different scenarios that both fit the geophysical data with a same likelihood but have different values for model materiality, with the model materiality being posed as an equality constraint in the inversion, wherein the model materiality is a functional of model parameters that characterize hydrocarbon potential of the subsurface region; analyzing a geophysical data misfit curve or geophysical data misfit likelihood curve, over a predetermined range of values of the model materiality to identify the at least two subsurface property models that correspond to a high-side and low-side, respectively, for each of the at least two subsurface properties, with the high-side and low-side quantifying uncertainties in the subsurface properties; and prospecting for hydrocarbons in the subsurface region with the at least two models that correspond to the high-side and the low-side for each of the at least two subsurface properties.

Reservoir materiality bounds from seismic inversion

A computer-implemented method for determining rock and fluid parameters of a subsurface region from measured seismic reflection data, said method including: generating, with a computer, a geophysical data volume by combining a plurality of angle stacks obtained from the measured seismic reflection data and geophysical property data obtained from a full wavefield inversion of the measured seismic reflection data; for each point of the geophysical data volume, determining, with a computer, a petrophysical model that is a probability of a rock state based on initial values of the rock and fluid parameters and the geophysical data volume; iteratively determining, using a computer, updated values for the rock and fluid parameters, wherein the iteratively determining includes determining a petrophysical parameter estimate for the rock and fluid parameters from the petrophysical model as constrained by the geophysical data volume and the initial values of the rock and fluid parameters, minimizing a misfit between the geophysical data volume and synthetic data generated from a forward modeling of the initial values of the rock and fluid parameters using a cost function that includes the petrophysical parameter estimate of the rock and fluid parameters, and repeating the iteratively determining until a predetermined stopping criteria is satisfied and final values for the rock and fluid parameters are generated, and each subsequent iteration of the iteratively determining replaces the initial values for the rock and fluid parameters with the updated values for the rock and fluid parameters from a previous iteration; determining, with a computer, uncertainty in the final values for the rock and fluid parameters; and exploring for or producing hydrocarbons using the final values for the rock and fluid parameters and there uncertainty.

Method for estimating petrophysical properties for single or multiple scenarios from several spectrally variable seismic and full wavefield inversion products

A method, including: generating a velocity model for a subsurface region of the Earth by using a full wavefield inversion process; generating an impedance model for the subsurface region of the Earth by using a full wavefield inversion process; and estimating pore pressure at a prediction site in the subsurface region by integrating the velocity model and the impedance model with a velocity-based pore pressure estimation process.

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Houston, TX, United States of America

Ratnanabha Sain