Improving GPU throughput of reservoir simulations using NVIDIA MPS and MIG

Author(s):  
R. Gandham ◽  
Y. Zhang ◽  
K. Esler ◽  
V. Natoli
2020 ◽  
Author(s):  
Haakon Hoegstoel ◽  
Jacob Stoeren ◽  
Magne Sjaastad ◽  
Gaute Lindkvist

2003 ◽  
Vol 129 (6) ◽  
pp. 443-457 ◽  
Author(s):  
John T. Hickey ◽  
Marchia V. Bond ◽  
Thomas K. Patton ◽  
Kevin A. Richardson ◽  
Paul E. Pugner

2005 ◽  
Vol 17 (11) ◽  
pp. 1387-1414 ◽  
Author(s):  
Manish Parashar ◽  
Rajeev Muralidhar ◽  
Wonsuck Lee ◽  
Dorian Arnold ◽  
Jack Dongarra ◽  
...  

2021 ◽  
Author(s):  
Hans Christian Walker ◽  
Anton Shchipanov ◽  
Harald Selseng

Abstract The Johan Sverdrup field located on the Norwegian Continental Shelf (NCS) started its production in October 2019. The field is considered as a pivotal development in the view of sustainable long-term production and developments on the NCS as well as creating jobs and revenue. The field is operated with advanced well and reservoir surveillance systems including Permanent Downhole Gauges (PDG), Multi-Phase Flow-Meters (MPFM) and seismic Permanent Reservoir Monitoring (PRM). This provides an exceptional basis for reservoir characterization and permanent monitoring. This study focuses on reservoir characterization to improve evaluations of sand permeability-thickness and fault transmissibility. Permanent monitoring of the reservoir with PDG / MPFM has provided an excellent basis for applying different methods of Pressure Transient Analysis (PTA) including analysis of well interference and time-lapse PTA. Interpretation of pressure transient data is today based on both analytical and numerical reservoir simulations (fit-for-purpose models). In this study, such models of the Johan Sverdrup reservoir regions have been assembled, using geological and PVT data, results of seismic interpretations and laboratory experiments. Uncertainties in these data were used to guide and frame the scope of the study. The interference analysis has confirmed communication between the wells located in the same and different reservoir regions, thus revealing hydraulic communication through faults. Sensitivities using segment reservoir simulations of the interference tests with different number of wells have shown the importance of including all the active wells, otherwise the interpretation may give biased results. The estimates for sand permeability-thickness as well as fault leakage obtained from the interference analysis were further applied in simulations of the production history using the fit-for-purpose reservoir models. The production history contains many pressure transients associated with both flowing and shut-in periods. Time-lapse PTA was focused on extraction and history matching of these pressure transients. The simulations have provided reasonable match of the production history and the time-lapse pressure transients including derivatives. This has confirmed the results of the interference analysis for permeability-thickness and fault leakage used as input for these simulations. Well interference is also the dominating factor driving the pressure transient responses. Drainage area around the wells is quickly established for groups of the wells analyzed due to the extreme permeability of the reservoir. It was possible to match many transient responses with segment models, however mismatch for some wells can be explained by the disregard of wells outside the segments, especially injectors. At the same time, it is a useful indication of communication between the regions. The study has improved reservoir characterization of the Johan Sverdrup field, also contributing to field implementation of combined PTA methods.


2021 ◽  
Author(s):  
Carlo Cristiano Stabile ◽  
Marco Barbiero ◽  
Giorgio Fighera ◽  
Laura Dovera

Abstract Optimizing well locations for a green field is critical to mitigate development risks. Performing such workflows with reservoir simulations is very challenging due to the huge computational cost. Proxy models can instead provide accurate estimates at a fraction of the computing time. This study presents an application of new generation functional proxies to optimize the well locations in a real oil field with respect to the actualized oil production on all the different geological realizations. Proxies are built with the Universal Trace Kriging and are functional in time allowing to actualize oil flows over the asset lifetime. Proxies are trained on the reservoir simulations using randomly sampled well locations. Two proxies are created for a pessimistic model (P10) and a mid-case model (P50) to capture the geological uncertainties. The optimization step uses the Non-dominated Sorting Genetic Algorithm, with discounted oil productions of the two proxies, as objective functions. An adaptive approach was employed: optimized points found from a first optimization were used to re-train the proxy models and a second run of optimization was performed. The methodology was applied on a real oil reservoir to optimize the location of four vertical production wells and compared against reference locations. 111 geological realizations were available, in which one relevant uncertainty is the presence of possible compartments. The decision space represented by the horizontal translation vectors for each well was sampled using Plackett-Burman and Latin-Hypercube designs. A first application produced a proxy with poor predictive quality. Redrawing the areas to avoid overlaps and to confine the decision space of each well in one compartment, improved the quality. This suggests that the proxy predictive ability deteriorates in presence of highly non-linear responses caused by sealing faults or by well interchanging positions. We then followed a 2-step adaptive approach: a first optimization was performed and the resulting Pareto front was validated with reservoir simulations; to further improve the proxy quality in this region of the decision space, the validated Pareto front points were added to the initial dataset to retrain the proxy and consequently rerun the optimization. The final well locations were validated on all 111 realizations with reservoir simulations and resulted in an overall increase of the discounted production of about 5% compared to the reference development strategy. The adaptive approach, combined with functional proxy, proved to be successful in improving the workflow by purposefully increasing the training set samples with data points able to enhance the optimization step effectiveness. Each optimization run performed relies on about 1 million proxy evaluations which required negligible computational time. The same workflow carried out with standard reservoir simulations would have been practically unfeasible.


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