公开(公告)号：US20230408718A1

公开(公告)日：2023-12-21

申请号：US17807100

申请日：2022-06-15

Applicant: ARAMCO SERVICES COMPANY

Inventor： Yong Ma ,  Weichang Li

IPC: G01V1/30 ,  G01V1/104 ,  G01V1/28

CPC classification number: G01V1/301 ,  G01V1/303 ,  G01V1/104 ,  G01V1/282 ,  G01V2210/6222

Abstract: A method which includes obtaining an initial velocity model and perturbing the initial velocity model to form a first plurality of velocity models. The method includes using a forward model to simulate seismic data sets from the first plurality of velocity models and transforming the seismic data sets to the wavenumber-time domain. The method includes training a machine-learned model using the first plurality of velocity models and the transformed seismic data sets, wherein the machine-learned model is configured to accept transformed seismic data. The method includes obtaining a second seismic data set for a subsurface region of interest, wherein the second seismic data set is acquired according to a second survey configuration and transforming the second seismic data set to the wavenumber-time domain. The method further includes processing the second transformed data set with the trained machine-learned model to predict a second velocity model for the subsurface region of interest.

公开(公告)号：US20250044469A1

公开(公告)日：2025-02-06

申请号：US18362720

申请日：2023-07-31

Applicant: ARAMCO SERVICES COMPANY

Inventor： Yong Ma ,  Weichang Li ,  Lei Fu

IPC: G01V1/28 ,  E21B44/00 ,  G01V1/30 ,  G06F30/27

Abstract: A system for enhancing traveltime information in a seismic dataset and determining a velocity model. The system includes a first initial velocity model, a forward modelling procedure, a machine-learned model, a drilling system with a wellbore planning system, and a computer. The computer is configured to: receive a non-synthetic seismic data set for a subsurface region of interest; perturb the first initial velocity model forming a first plurality of velocity models; simulate, with the forward modelling procedure, a first plurality of seismic data sets; form a first plurality of transformed seismic data sets with enhanced traveltime; train the machine-learned model using the first plurality of velocity models and the first plurality of transformed seismic data sets; transform the non-synthetic seismic data set to a non-synthetic transformed seismic data set; and process the non-synthetic seismic data set with the trained machine-learned model to predict a velocity model for the subsurface region.