Invention Application
- Patent Title: DEEP REINFORCEMENT LEARNING FOR FIELD DEVELOPMENT PLANNING OPTIMIZATION
-
Application No.: US17534076Application Date: 2021-11-23
-
Publication No.: US20220164657A1Publication Date: 2022-05-26
- Inventor: Jincong HE , Xian-Huan WEN , Meng TANG , Chaoshun HU , Shusei TANAKA , Kainan WANG
- Applicant: Chevron U.S.A. Inc.
- Applicant Address: US CA San Ramon
- Assignee: Chevron U.S.A. Inc.
- Current Assignee: Chevron U.S.A. Inc.
- Current Assignee Address: US CA San Ramon
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

Abstract:
Embodiments of generating a field development plan for a hydrocarbon field development are provided herein. One embodiment comprises generating a plurality of training reservoir models of varying values of input channels of a reservoir template; normalizing the varying values of the input channels to generate normalized values of the input channels; constructing a policy neural network and a value neural network that project a state represented by the normalized values of the input channels to a field development action and a value of the state respectively; and training the policy neural network and the value neural network using deep reinforcement learning on the plurality of training reservoir models with a reservoir simulator as an environment such that the policy neural network generates a field development plan. A field development plan may be generated for a target reservoir on the reservoir template using the trained policy network and the reservoir simulator.
Information query