A Parallel Reservoir Simulator for Large-Scale Reservoir Simulation

Doğru, Ali H.; Sunaidi, H.A.; Fung, Larry S.K.; Habiballah, W.A.; Al-Zamel, Nabil; Li, K.G.

doi:10.2118/75805-pa

Cited by 75 publications

(25 citation statements)

References 21 publications

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“…Parallel processing with high performance computing clusters can alleviate these challenges to a good extent. Wang et al (1997), Zhang et al (2001), Dogru et al (2002), Gai et al (2003), andDeBaun et al (2005) demonstrated the necessity, advantages, and applicability of using parallel processing for large-scale reservoir simulations.…”

Section: Parallel Processingmentioning

confidence: 99%

Development of an Efficient Embedded Discrete Fracture Model for 3D Compositional Reservoir Simulation in Fractured Reservoirs

et al. 2013

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Summary Many naturally fractured reservoirs around the world have depleted significantly, and improved-oil-recovery (IOR) processes are necessary for further development. Hence, the modeling of fractured reservoirs has received increased attention recently. Accurate modeling and simulation of naturally fractured reservoirs (NFRs) is still challenging because of permeability anisotropies and contrasts. Nonphysical abstractions inherent in conventional dual-porosity and dual-permeability models make them inadequate for solving different fluid-flow problems in fractured reservoirs. Also, recent technologies for discrete fracture modeling may suffer from large simulation run times, and the industry has not used such approaches widely, even though they give more-accurate representations of fractured reservoirs than dual-continuum models. We developed an embedded discrete fracture model (DFM) for an in-house compositional reservoir simulator that borrows the dual-medium concept from conventional dual-continuum models and also incorporates the effect of each fracture explicitly. The model is compatible with existing finite-difference reservoir simulators. In contrast to dual-continuum models, fractures have arbitrary orientations and can be oblique or vertical, honoring the complexity of a typical NFR. The accuracy of the embedded DFM is confirmed by comparing the results with the fine-grid, explicit-fracture simulations for a case study including orthogonal fractures and a case with a nonaligned fracture. We also perform a grid-sensitivity study to show the convergence of the method as the grid is refined. Our simulations indicate that to achieve accurate results, the embedded discrete fracture model may only require moderate mesh refinement around the fractures and hence offers a computationally efficient approach. Furthermore, examples of waterflooding, gas injection, and primary depletion are presented to demonstrate the performance and applicability of the developed method for simulating fluid flow in NFRs.

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Section: Parallel Processingmentioning

confidence: 99%

Development of an Efficient Embedded Discrete Fracture Model for 3D Compositional Reservoir Simulation in Fractured Reservoirs

et al. 2013

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“…Many reservoir simulators have been developed by different companies, universities and research centers. The majority of them are commercially available or have been presented in the literature [3]- [10]. Regardless of how precise these simulators are, the uncertainties in the measured reservoir characteristics which are used as their inputs may cause errors in the production forecast [11], [12].…”

Section: Introductionmentioning

confidence: 99%

Effects of Flow Measurement Errors on Oil and Gas Production Forecasts

Sadri

Shariatipour

Hunt

2017

Computational and Experimental Methods in Multiphase and Complex Flow IX

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Different flow meter technologies are used to monitor the output of oil and gas wells. Although flowmeter accuracy has generally improved over time, there remain substantial uncertainties, particularly in multiphase flow. These errors could potentially be greater where older meters are being used for calibration, and/or maintenance is difficult. Consequently, the associated errors with the recorded data could be out of specification in such cases. One use of the well flow data is to improve parameter estimates for important characteristics of reservoirs such as porosity and permeability. Therefore, any errors in flow measurement influence the results of a reservoir simulation and production forecasts. However, the impact of flow measurement errors on the forecast of oil and gas production has not been considered before. In this study, the effects of using out-of-specification errors on the predicted reservoir production have been investigated. As a test case, the simulated production results of a reservoir with known characteristics were considered to be the actual flow rate values. Then, two sets of data were generated by applying errors up to 5% and 10%, respectively, to the flow rates and the resulting values were used in a history matching exercise to modify the predictions of the simulations for the same reservoir with incorrect porosity and permeability parameters. The errors in the first and second sets of data were considered to be within and without the specification, respectively. The results show that when errors are within the specification, the corrected porosity and permeability values have less than a 2.2% and 2.5% error, which cause minor deviations of up to 2.3% in the production forecast. However, for the second set of data, when the errors are increased up to 5% more than the specification, the corrected porosity, permeability and production forecast deviate significantly up to 10.8 %, 10.1% and 12.4% from their respective reference values.

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“…Since 1980s, various of parallel simulators were developed (Li et al, 1995;Wheeler and Smith, 1989;Rutledge et al, 1991;Shiralkar et al, 1997;Parashar et al, 1997;Kaarstad et al, 1995;Killough and Bhogeswara, 1991;Killough et al, 1997). In (Dogru et al, 2002(Dogru et al, , 2009), Dogru et al developed a parallel simulator, GigaPOWERS, which has been successfully applied to a case with one billion gird cells, and a truncated Neumann series preconditioner is developed. In (DeBaun et al, 2005), an objectoriented, component-based architecture is designed, built on which a black oil simulator and a compositional simulator are developed.…”

Section: Introductionmentioning

confidence: 99%