US 12,422,581 B2
System and method for prediction of reservoir parameters with uncertainty quantification
Ke Wang, Sugar Land, TX (US); Jinsong Chen, Fulshear, TX (US); and Yijie Zhou, Richmond, TX (US)
Assigned to CHEVRON U.S.A. INC., San Ramon, CA (US)
Filed by Chevron U.S.A. Inc., San Ramon, CA (US)
Filed on Dec. 21, 2022, as Appl. No. 18/069,865.
Prior Publication US 2024/0210584 A1, Jun. 27, 2024
Int. Cl. G01V 1/30 (2006.01); G01V 1/28 (2006.01); G01V 1/34 (2006.01); G06N 3/091 (2023.01)
CPC G01V 1/30 (2013.01) [G01V 1/282 (2013.01); G01V 1/345 (2013.01); G06N 3/091 (2023.01)] 12 Claims
OG exemplary drawing
 
1. A computer-implemented method for efficient seismic inversion that does not require a user-specified low frequency model (LFM) as input, comprising:
a. receiving, at one or more computer processors, well logs and seismic angle stacks representative of a subsurface volume of interest;
b. deriving, via the one or more computer processors, rock physics models from the well logs and the seismic angle stacks;
c. performing, via the one or more computer processors, low frequency Markov Chain Monte Carlo (MCMC) processes on the rock physics models to generate low frequency models (LFMs) of rock properties, wherein the low frequency models (LFMs) are lower than 15 Hz;
d. training a deep neural network using the LFMs, the rock physics models, and the seismic angle stacks as training pairs of {log properties, seismic data} to generate a trained neural network;
e. providing a seismic dataset to the trained neural network to generate a high frequency rock property model;
f. performing broad-band MCMC processes on the high frequency rock property model to generate an ensemble of high frequency realizations of rock properties; and
g. using the ensemble of high frequency realizations of rock properties to identify hydrocarbon deposits and recover hydrocarbons.