The Implementation of Hybrid Parallel Computation for Complex and Fine Reservoir Model Using Cluster Technology

2021 ◽  
Author(s):  
B. Darmawan
Keyword(s):  
Modeling And Simulation ◽  
Message Passing Interface ◽  
Cluster Computing ◽  
Performance Test ◽  
Hybrid Approach ◽  
Reservoir Modeling ◽  
Computing Technology ◽  
Reservoir Model ◽  
Cluster Technology ◽  
Simulation Time

Pertamina EP plays an important role in maintaining the oil production supply for national energy stability. Thus, they bear a great responsibility to accelerate all the development plans and execute them in timely manner. However, there is big challenge in the realization of those plans since they are not fully equipped with the advance computing technology to boost the reservoir modeling and simulation phase. Therefore, the effort on finalizing and executing of 33 Plan of development (POD) projects within 5 years was looked like a never-ending project. To face the challenge, Pertamina EP evaluated the possibility to create a cluster technology that can accommodate high intensity of simulation numbers and high load of simulation process. The evaluation process covers: compiling, sorting and selecting the analog reservoir model (highest grid number and longest simulation time), benchmarking and performance test to get the most optimum cluster configuration. Supercomputer was then procured and set based on the optimized model, then completed by implementing the test on three most extreme POD models. This paper described the success story and innovation of a complex simulation and finer scale reservoir model using the hybrid parallel-computing technology with a set of 8 nodes high performing computer. Three models were tested with satisfying results. This paper discusses the parallel scalability of complex computing systems of multi-CPU clusters. Multi-CPU distributed memory computing system is proven to be able to improve and accelerate the reservoir modeling and simulation time, when it is used in combination with a new so called “hybrid” approach. In this approach, the common Message Passing Interface (MPI) synchronization between the cluster nodes is being interleaved with a shared memory system thread-based synchronization at the node level. The model with the longest simulation time has been accelerated by magnitude of 60%. The most exhausted model with highest number of simulation steps has been accelerated by magnitude of 80%. The model with the greatest number of grid (21.7 million active grids) has finally finished its simulation just in 27 minutes where previously was impossible to have it open and run. The successful study case is then followed by the implementation of the cluster computing technology for two pilot POD projects which led to the very good result. With this improvement, Pertamina EP can finally perform the probabilistic simulation as recommended by SKKMIGAS in PTK Rev-2/2018. It is now possible to run all 33 structures of multiple reservoir realizations for each POD.

INTEGRATED TECHNOLOGY OF BROWN FIELD STUDY TO INCREASE PRODUCTION AND OIL RECOVERY

2020 ◽  
pp. 61-66
Author(s):  
I.A. Zhdanov ◽  
E.S. Pakhomov ◽  
A.M. Aslanyan ◽  
R.R. Farakhova ◽  
D.N. Gulyaev ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Field Studies ◽  
Development Planning ◽  
Reservoir Modeling ◽  
Integrated Analysis ◽  
Well Testing ◽  
Reservoir Model ◽  
Scenario Development ◽  
Sweep Efficiency ◽  
High Level

Paper presents the results of integrated analysis of historically available data and additional field studies at the brown field. The results of the analysis increase the reliability of the geological and hydrodynamic reservoir model, current recovery and identification of areas, which are most promising for production enhancement operations for production increase and recovery increase. The integrated analysis of available data includes such tools as prelaminar data analysis of production and pressure changes (Prime) for high level reserves localization, multiwell retrospective testing (MRT) and pulsecode testing (PCT) for evaluation of reservoir geology, sweep efficiency and current reservoir saturation, geological and hydrodynamic reservoir modeling including petrofacies and model adaptation to the production logging, MRT, PCT and well-testing findings, multi-scenario development planning (MSDP) for the most economically profitable operations recommendation and supervision of their implementation. MSDP is based on the usage by several teams of reservoir engineers web-facility PloyPlan, which automatically translates the field activities (like drilling, workover, conversion, surveillance, etc.) into the model runs and reverts back with production and surveillance results and financial statements, based on which it is easy to choose the most profitable field operations. Up to today Prime analysis, field studies and reservoir model calibration on their results are finished.

Optimizing Field Performance Using Reservoir Modeling and Simulation

2001 ◽  
Author(s):  
Mohamed A. Naguib ◽  
Khaled A. Aziz ◽  
Ahmed Hussein
Keyword(s):  
Modeling And Simulation ◽  
Field Performance ◽  
Reservoir Modeling

Hybrid Approach to Reservoir Modeling Based on Modern CPU and GPU Computational Platforms (Russian)

2017 ◽  
Author(s):  
Alexey Telishev ◽  
Kirill Bogachev ◽  
Vasilii Shelkov ◽  
Dmitry Eydinov ◽  
Hau Tran
Keyword(s):  
Hybrid Approach ◽  
Reservoir Modeling

Optimal dynamic rock-fluid physics template validated by petroelastic reservoir modeling

Geophysics ◽  
2011 ◽  
Vol 76 (6) ◽  
pp. O45-O58 ◽  
Author(s):  
Alireza Shahin ◽  
Robert Tatham ◽  
Paul Stoffa ◽  
Kyle Spikes
Keyword(s):  
Sensitivity Analysis ◽  
Acoustic Impedance ◽  
Velocity Ratio ◽  
Rapid Change ◽  
Time Lapse ◽  
Seismic Attributes ◽  
Reservoir Modeling ◽  
Reservoir Model ◽  
Reservoir Properties ◽  
Fluid Saturation

Separation of fluid pore pressure and saturation using inverted time-lapse seismic attributes is a mandatory task for field development. Multiple pairs of inversion-derived attributes can be used in a crossplot domain. We performed a sensitivity analysis to determine an optimal crossplot, and the validity of the separation is tested with a comprehensive petroelastic reservoir model. We simulated a poorly consolidated shaly sandstone reservoir based on a prograding near-shore depositional environment. A model of effective porosity is first simulated by Gaussian geostatistics. Well-known theoretical and experimental petrophysical correlations were then efficiently combined to consistently simulate reservoir properties. Next, the reservoir model was subjected to numerical simulation of multiphase fluid flow to predict the spatial distributions of fluid saturation and pressure. A geologically consistent rock physics model was then used to simulate the inverted seismic attributes. Finally, we conducted a sensitivity analysis of seismic attributes and their crossplots as a tool to discriminate the effect of pressure and saturation. The sensitivity analysis demonstrates that crossplotting of acoustic impedance versus shear impedance should be the most stable way to separate saturation and pressure changes compared to other crossplots (e.g., velocity ratio versus acoustic impedance). We also demonstrated that the saturation and pressure patterns were detected in most of the time-lapse scenarios; however, the saturation pattern is more likely detectable because the percentage in pressure change is often lower than that of the saturation change. Imperfections in saturation and pressure patterns exist in various forms, and they can be explained by the interaction of saturation and pressure, the diffusive nature of pressure, and rapid change in pressure due to production operations.

Well location optimization of Zama reservoir using top down reservoir modeling(TDRM)

2020 ◽  
Author(s):  
Taehun Lee ◽  
Kyungbook Lee ◽  
Hyunsuk Lee ◽  
Wonsuk Lee
Keyword(s):  
Artificial Intelligence ◽  
Human Life ◽  
Oil Field ◽  
Oil Fields ◽  
Reservoir Modeling ◽  
Reservoir Model ◽  
Location Optimization ◽  
Well Location ◽  
Artificial Intelligence Technology ◽  
Short Time

<p>Artificial intelligence is applied in various fields of human life and is being actively studied and applied in the oil fields. Especially, the digital oil field, which has recently been spotlighted, is required to simulate the reservoir using artificial intelligence. However, there is almost little research to date. Therefore, in this study, we applied TDRM using artificial intelligence technology to Zama field located on the land of Canada. The required static and dynamic data were obtained from Accumap, a Canadian well information S/W. As a result, the reservoir model was constructed successfully and the well location optimization could be performed in a short time using TDRM.</p>

A Hybrid Mpi-Openmp Implementation of an Implicit Finite-Element Code on Parallel Architectures

2002 ◽  
Vol 16 (4) ◽  
pp. 371-393 ◽  
Author(s):  
G. Mahinthakumar ◽  
F. Saied
Keyword(s):  
Finite Element ◽  
Hybrid Model ◽  
Message Passing ◽  
Message Passing Interface ◽  
Hybrid Approach ◽  
Parallel Architectures ◽  
Finite Element Code ◽  
Multiple Threads ◽  
Smp Clusters ◽  
Performance Results

Summary The hybrid MPI-OpenMP model is a natural parallel programming paradigm for emerging parallel architectures that are based on symmetric multiprocessor (SMP) clusters. This paper presents a hybrid implementation adapted for an implicit finite-element code developed for groundwater transport simulations. The original code was parallelized for distributed memory architectures using MPI (Message Passing Interface) using a domain decomposition strategy. OpenMP directives were then added to the code (a straightforward loop-level implementation) to use multiple threads within each MPI process. To improve the OpenMP performance, several loop modifications were adopted. The parallel performance results are compared for four modern parallel architectures. The results show that for most of the cases tested, the pure MPI approach outperforms the hybrid model. The exceptions to this observation were mainly due to a limitation in the MPI library implementation on one of the architectures. A general conclusion is that while the hybrid model is a promising approach for SMP cluster architectures, at the time of this writing, the payoff may not be justified for converting all existing MPI codes to hybrid codes. However, improvements in OpenMP compilers combined with potential MPI limitations in SMP nodes may make the hybrid approach more attractive for a broader set of applications in the future.

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