SYSTEM AND METHOD FOR DERIVING HIGH-RESOLUTION SUBSURFACE RESERVOIR PARAMETERS

    公开(公告)号:US20200217978A1

    公开(公告)日:2020-07-09

    申请号:US16724738

    申请日:2019-12-23

    Abstract: A method is described for deriving high-resolution reservoir properties for a subsurface reservoir. The method may include receiving a seismic dataset; inverting the seismic dataset to generate an ensemble of coarse-scale seismic parameters, wherein the inverting may use one of Bayesian models with Markov Chain Monte Carlo (MCMC) sampling, simulated annealing, partial swarm, or analytic Bayes formulations; receiving fine-scale lithotype models; developing deep learning neural networks based on transfer learning using the fine-scale lithotype models to generate a conditional probability distribution of high-resolution reservoir parameters; generating an ensemble of high-resolution reservoir parameters using the deep learning neural network to condition the ensemble of coarse-scale seismic parameters; and displaying, on a user interface, the ensemble of high-resolution reservoir parameters. The method is executed by a computer system.

    Systems And Methods For Using Probabilities of Lithologies In an Inversion

    公开(公告)号:US20190302295A1

    公开(公告)日:2019-10-03

    申请号:US15943535

    申请日:2018-04-02

    Abstract: Systems and methods for training a model that uses probabilities of lithologies as prior information in an inversion are disclosed. Exemplary implementations may: obtain training data, the training data including (i) subsurface map data sets, and (ii) known lithologies; obtain an initial seismic mapping model; generate a conditioned seismic mapping model by training the initial seismic mapping model; store the conditioned seismic mapping model; obtain a target subsurface map data set; apply the conditioned seismic mapping model to generate a classified lithology map data set; apply an inversion to the classified lithology map data set to generate volumes of lithologies; generate an image that represents the volumes of lithologies; display the image.

    SYSTEM AND METHOD FOR STOCHASTIC FULL WAVEFORM INVERSION

    公开(公告)号:US20230099919A1

    公开(公告)日:2023-03-30

    申请号:US17279375

    申请日:2021-03-15

    Abstract: A method is described for generating a subsurface model using stochastic full waveform inversion by receiving a seismic dataset representative of a subsurface volume of interest; performing stochastic full waveform inversion of the seismic dataset to generate a long wavelength subsurface model; and performing full waveform inversion of the seismic dataset using the long wavelength subsurface model as a starting model to generate an improved subsurface model. The method may further include performing seismic imaging of the seismic dataset using the improved subsurface model to generate a seismic image and identifying geologic features based on the seismic image. The method may be executed by a computer system.

    Systems and methods for using probabilities of lithologies in an inversion

    公开(公告)号:US10884150B2

    公开(公告)日:2021-01-05

    申请号:US15943535

    申请日:2018-04-02

    Abstract: Systems and methods for training a model that uses probabilities of lithologies as prior information in an inversion are disclosed. Exemplary implementations may: obtain training data, the training data including (i) subsurface map data sets, and (ii) known lithologies; obtain an initial seismic mapping model; generate a conditioned seismic mapping model by training the initial seismic mapping model; store the conditioned seismic mapping model; obtain a target subsurface map data set; apply the conditioned seismic mapping model to generate a classified lithology map data set; apply an inversion to the classified lithology map data set to generate volumes of lithologies; generate an image that represents the volumes of lithologies; display the image.

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