Application of sector modeling technology for giant reservoir simulations

Abstract

AbstractCurrently, to build models for dynamic simulations of large oil and gas fields, engineers have to upscale the original geological grid not to exceed limits set but by computer memory size, CPU performance, and by the capabilities of standard commercial software packages. As a result, the upscaled model often has a rather low level of detalization. Since upscaling inevitably generates additional simulation errors, the resulting simulation model can solve only a limited number of practical tasks. The coarsened models are typically used for strategic tasks – to find an appropriate field development system, understand fluid and gas migration processes, and plan future production for this field.Such upscaled models are rarely used for planning of risky, high cost and practically important tactical and operational tasks of field development management and production monitoring. It's ironic that oil and gas companies invest large sums of money on detalization of the reservoir geological description, and then have to drop this information in the process of hydrodynamic simulations. Engineers often call this paradox a "simulation scale problem". Since computer hardware performance increases exponentially in time, it is the technological level of software that becomes the main limitation factor.If one could build a coherent "hardware+software" solution to resolve flow dynamics in porous media for geological grids with tens and hundreds of millions of blocks without upscaling, the problem could be solved.In this article, the technology for constructing and effective handling of giant field models by application of sector modeling and advanced parallel algorithms is discussed. The important role of modern computer hardware architecture - especially processors and RAM designs is emphasized.The authors discuss practical aspects concerning model dimensions, simulation model calculation speed for the whole field model or for any of its parts, choice of optimal model cut into sections, and boundary condition setting methods.Technology application results are demonstrated for one of the world's biggest oil fields, with a geological model size of about 43 million grid blocks. The authors show that when the whole field is divided into a certain number of sector models, the sum of their calculation times may be substantially smaller than the full model calculation time. At the same time, if boundary conditions are included in simulations of subdomains, the spread in values of calculated production rates can be as small as 1%. The approach described in this paper appears to be efficient for history matching of large hydrodynamic models. It helps to reduce the time to completion for the project, and avoid the unnecessary modeling precision degradation caused by grid upscaling.