公开(公告)号：CA3024461A1

公开(公告)日：2017-11-23

申请号：CA3024461

申请日：2017-05-12

Applicant: REPSOL SA ,  IBM

Inventor： RODRIGUEZ TORRADO RUBEN ,  RIOS ALIAGA JESUS ,  DE PAOLA GIORGIO ,  EMBID DROZ SONIA MARIETTE

IPC: G06Q10/04 ,  G06Q50/06

Abstract: The present invention is related to a computer implemented method for generating an optimal field development plan (FDP) for the exploitation of oil and gas reservoirs when the available data of the reservoir is limited. The method generates a tree starting from a root node wherein each node represents a decision or an observation of the field. The tree generation comprises an specific manner of combining a search and a rollout process for exploring paths providing candidates of field development plans (FDP) and adding new nodes to the tree. The method reduces drastically the computational cost providing an affordable manner of estimating an optimal field development plan (FDP) before carrying out the exploitation of the reservoir.

公开(公告)号：CA2914465A1

公开(公告)日：2014-12-31

申请号：CA2914465

申请日：2014-06-27

Applicant: REPSOL SA ,  IBM

Inventor： EMBID DROZ SONIA ,  RODRIGUEZ TORRADO RUBEN ,  DE PAOLA GIORGIO ,  HEGAZY MOHAMED ,  ECHEVERRIA CIAURRI DAVID ,  FLACH BRUNO ,  MELLO ULISSES

IPC: G06Q50/02

Abstract: The present invention is related to generating scenarios of hydrocarbon reservoirs based on limited amount of information on a target hydrocarbon reservoir, and more particularly to automatically supplying missing parameters and an uncertainty associated with each supplied parameter allowing to valuating the target hydrocarbon reservoir.

公开(公告)号：CA2988202A1

公开(公告)日：2016-12-08

申请号：CA2988202

申请日：2016-06-03

Applicant: REPSOL SA

Inventor： RODRIGUEZ TORRADO RUBEN ,  DE PAOLA GIORGIO ,  EMBID DROZ SONIA MARIETTE

IPC: G06Q10/04 ,  G06Q10/06

Abstract: The present invention is related to a method of generating a production strategy for the development of a reservoir of hydrocarbon in a natural environment by solving a minimization problem involving, among others, decisional variables, in such a way said decisional variables are reduced or even eliminated by combining them with other continuous variables. The reduction of decisional variables provides a high reduction of the computational cost. The elimination of all decisional variables allow a further reduction of the computational cost as solvers such as Mixed Integer Nonlinear Programming allowing the use of decisional variables that are not needed anymore. A particular case of decisional variables are binary variables.