Application of sector modeling technology for giant reservoir simulations

Abstract

Currently, 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.

Representative Sector Modeling and Waterflooding Performance in Rumaila Oilfield

“…Depending on the well logs response and final well report (FWR), FZI values were distributed among the reservoir major units, where the unit with good properties has taken a higher FZI value and so on. Based on these subdivisions, the permeability value was obtained using equation (2)(3)(4)(5) and FZI values were specified for each subunit. Figure-3 shows the plot of core and predicted permeability versus depth, which gives an acceptable agreement between core permeability and K-calculated from FZI approach.…”

“…Developing a full simulation study of large oil fields requires upscaling of the geological models that might minimize the level of detalization and inevitably. However, additional errors can be resulted in the simulation process due to this upscaling [4]. Moreover, the simulation runs for large fields would take long time.…”

Dynamic Modeling of Samotlor Field Using High Resolution Model Grids

“…The models were run using ordinary commercial release of tNavigator hydrodynamic simulator, which uses a hybrid parallelization algorithm (MPIϩOS threads) for calculation acceleration (16], [17], [18]). The most complex calculations were performed on the RFD cluster containing 64 nodes with 1280 CPU cores of Xeon E5-2680v2 2.8GHz Intel processors.…”

Dynamic Modeling of Samotlor Field Using High Resolution Model Grids (Russian)

“…Одной из главных задач моделирования Самотлорского месторождения является создание согласованной системы секторного и полномасштабного моделирования на основе единой гидродинамической модели высокого разрешения без апскейлинга ( [17]). Это позволит решать и глобальные, и локальные задачи в рамках одной концептуальной геолого-гидродинамической модели.…”

“…Для расчета моделей применялся коммерческий гидродинамический симулятор tNavigator использующий гибридный (MPI+OS threads) алгоритм распараллеливания (16], [17], [18]). Наиболее сложные варианты моделей рассчитывались на кластере RFD состоящем из 64 узлов с 1280 расчетных ядер процессора Xeon E5-2680v2 2.8GHz компании Intel.…”