Constrained optimization for well placement planning

Abstract

A method, apparatus and program product utilize a constrained optimization framework to generate a well placement plan based on a reservoir model. Candidate well placement plans are generated from control vectors proposed by an optimization engine to optimize based upon an objective function that generally involves an access to a reservoir simulator. Inexpensive constraints that are not based on computation of the objective function are evaluated prior to accessing the reservoir simulator to avoid unnecessary accesses to the reservoir simulator for candidate well placement plans determined to be infeasible in view of the inexpensive constraints. For candidate well placement plans that are determined to be feasible based upon the inexpensive constraints, the objective function may be calculated and additional expensive constraints may thereafter be evaluated to further determine the feasibility of candidate well placement plans.

What is claimed is: 
     
         1 . A method for well placement planning, the method comprising:
 generating a control vector comprising a plurality of control variables over which to optimize;   translating the control vector to a candidate well placement plan;   performing a first feasibility evaluation for the candidate well placement plan against one or more inexpensive constraints; and   in response to determining a feasibility of the candidate well placement plan from the first feasibility evaluation:   computing a result for an objective function based upon the candidate well placement plan using a reservoir simulator; and   performing a second feasibility evaluation for the candidate well placement plan by evaluating the computed result for the objective function based upon the candidate well placement plan against one or more expensive constraints.   
     
     
         2 . The method of  claim 1 , further comprising performing a feasibility evaluation for the control vector against one or more linear constraints prior to translating the control vector, wherein translating the control vector is only performed in response to determining a feasibility of the control vector from the third feasibility evaluation. 
     
     
         3 . The method of  claim 1 , wherein the control vector comprises an initial control vector, and wherein the method further comprises generating the initial control vector by translating an initial well placement plan to the initial control vector. 
     
     
         4 . The method of  claim 1 , further comprising, in response to determining an infeasibility of the candidate well placement plan from the first feasibility evaluation, bypassing computing the result for the objective function and performing the second feasibility evaluation. 
     
     
         5 . The method of  claim 1 , further comprising, in response to determining a feasibility of the candidate well placement plan from the second feasibility evaluation, determining that the candidate well placement plan is a feasible well placement plan. 
     
     
         6 . The method of  claim 1 , further comprising, for each of a plurality of control vectors, performing a trial processing operation associated therewith, wherein each trial processing operation comprises:
 determining feasibility for the associated control vector against one or more linear constraints; and   in response to determining a feasibility of the associated control vector against the one or more linear constraints:   translating the associated control vector to an associated candidate well placement plan;   performing the first feasibility evaluation for the associated candidate well placement plan against the one or more inexpensive constraints; and   in response to determining a feasibility of the associated candidate well placement plan from the first feasibility evaluation:   computing a result for the objective function based upon the associated candidate well placement plan using the reservoir simulator; and   performing the second feasibility evaluation for the associated candidate well placement plan by evaluating the computed result for the objective function based upon the associated candidate well placement plan against the one or more expensive constraints.   
     
     
         7 . The method of  claim 6 , further comprising, generating at least one of the plurality of control vectors by extrapolating from a prior control vector based at least in part on a feasibility evaluation performed during a trial processing operation for the prior control vector. 
     
     
         8 . The method of  claim 7 , wherein the prior control vector is associated with an associated candidate well placement plan determined as infeasible, and wherein extrapolating from the prior control vector is based upon a result of at least one feasibility evaluation performed during the trial processing operation for the prior control vector. 
     
     
         9 . The method of  claim 7 , further comprising terminating well placement planning after performing the trial processing operation for each of the plurality of control vectors in response to a termination condition, wherein the termination condition is based on a determination that a maximum number of trial processing operations have been performed, a determination that improvement in the objective function has stalled, or a combination thereof. 
     
     
         10 . The method of  claim 1 , wherein the reservoir simulator comprises an analytical reservoir simulator that accesses a coarse scale reservoir simulation model. 
     
     
         11 . The method of  claim 10 , further comprising generating the coarse scale reservoir simulation model by upscaling a fine scale reservoir geology model. 
     
     
         12 . The method of  claim 1 , wherein the objective function includes one or more of net present value, return on investment, profitability, production index, or combinations thereof. 
     
     
         13 . The method of  claim 1 , wherein computing the result of the objective function comprises computing a plurality of results for a plurality of realizations to account for uncertainty in the reservoir model, the method further comprising optimizing on a utility function based on the plurality of results computed for the plurality of realizations. 
     
     
         14 . The method of  claim 1 , wherein translating the control vector to the candidate well placement plan comprises identifying a plurality of target locations in a reservoir, determining a completion geometry for each target location, and determining a trajectory for each target location. 
     
     
         15 . The method of  claim 14 , wherein determining the completion geometry for a first target location among the plurality of target locations comprises determining at least one completion location based upon at least one property of a plurality of cells associated with the first target location and retrieved from a fine scale reservoir geology model. 
     
     
         16 . The method of  claim 15 , wherein the one or more inexpensive constraints includes a feasibility of the first target location based on a geometric relation to the fine scale reservoir geology model, wherein the geometric relation includes a minimum completion length, a minimum standoff relative to a fluid contact, a minimum distance to a fault, or a combination thereof. 
     
     
         17 . The method of  claim 15 , wherein the one or more inexpensive constraints includes a feasibility of the first target location based on a property of the fine scale reservoir geology model, wherein the property includes minimum porosity, minimum permeability, maximum water saturation, or a combination thereof. 
     
     
         18 . The method of  claim 1 , wherein performing the first feasibility evaluation for the candidate well placement plan against the one or more inexpensive constraints comprises performing anti-collision analysis on the candidate well placement plan. 
     
     
         19 . The method of  claim 1 , wherein the one or more inexpensive constraints includes one or more of dogleg severity, maximum inclination, maximum reach, number of platforms, number of wells, flowing producers, slot number, platform location, minimum tie point separation, minimum completion spacing, or combinations thereof. 
     
     
         20 . The method of  claim 1 , wherein the one or more expensive constraints includes one or more of sub-economic wells, flowing producers or a combination thereof. 
     
     
         21 . The method of  claim 1 , wherein the control vector comprises one or more of target location coordinates, tie point coordinates, azimuth of a pattern, pattern spacing, or combinations thereof. 
     
     
         22 . An apparatus, comprising:
 at least one processing unit; and   program code configured upon execution by the at least one processing unit to perform well placement planning by:   generating a control vector comprising a plurality of control variables over which to optimize;   translating the control vector to a candidate well placement plan;   performing a first feasibility evaluation for the candidate well placement plan against one or more inexpensive constraints; and   in response to determining a feasibility of the candidate well placement plan from the first feasibility evaluation:   computing a result for an objective function based upon the candidate well placement plan using a reservoir simulator; and   performing a second feasibility evaluation for the candidate well placement plan by evaluating the computed result for the objective function based upon the candidate well placement plan against one or more expensive constraints.   
     
     
         23 . A program product, comprising:
 a computer readable medium; and   program code stored on the computer readable medium and configured upon execution by at least one processing unit to perform well placement planning by:   generating a control vector comprising a plurality of control variables over which to optimize;   translating the control vector to a candidate well placement plan;   performing a first feasibility evaluation for the candidate well placement plan against one or more inexpensive constraints; and   in response to determining a feasibility of the candidate well placement plan from the first feasibility evaluation:   computing a result for an objective function based upon the candidate well placement plan using a reservoir simulator; and   performing a second feasibility evaluation for the candidate well placement plan by evaluating the computed result for the objective function based upon the candidate well placement plan against one or more expensive constraints.