Middle East Steamflood Field Optimization Demonstration Project

Behm, Ed; Asimi, Mohammed Al; Maskari, Sara Al; Juna, Wladimir; Klíe, Héctor; Le, Duc H.; Lutidze, Giorgiy; Rastegar, Reza; Reynolds, Albert C.; Tathed, Vinit; Younis, Rami M.; Zhang, Yuchen

doi:10.2118/197751-ms

Cited by 10 publications

(1 citation statement)

References 7 publications

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“…The family of interwell numerical simulation models (INSIM) focus on the dynamic behavior and interactions between multiple wells and use analytical or semi-analytical methods to evolve pressures and fluid compositions within each interwell connection [18][19][20][21][22]. A more general approach, referred to by different authors as StellNet/GPSNet/FlowNet, is to use standard finite-volume methods to represent the interwell connections and also allow direct fluid communication among different flow paths without going through the wells [23][24][25][26][27][28][29]. Compared with these interwell models, CGNet gives a richer network that has more free parameters per grid cell and a larger set of network paths connecting each pair of wells.…”

Section: Introductionmentioning

confidence: 99%

Data-driven modelling with coarse-grid network models

Lie

Krogstad

2023

Comput Geosci

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We propose to use a conventional simulator, formulated on the topology of a coarse volumetric 3D grid, as a data-driven network model that seeks to reproduce observed and predict future well responses. The conceptual difference from standard history matching is that the tunable network parameters are calibrated freely without regard to the physical interpretation of their calibrated values. The simplest version uses a minimal rectilinear mesh covering the assumed map outline and base/top surface of the reservoir. The resulting CGNet models fit immediately in any standard simulator and are very fast to evaluate because of the low cell count. We show that surprisingly accurate network models can be developed using grids with a few tens or hundreds of cells. Compared with similar interwell network models (e.g., Ren et al., 2019, 10.2118/193855-MS), a typical CGNet model has fewer computational cells but a richer connection graph and more tunable parameters. In our experience, CGNet models therefore calibrate better and are simpler to set up to reflect known fluid contacts, etc. For cases with poor vertical connection or internal fluid contacts, it is advantageous if the model has several horizontal layers in the network topology. We also show that starting with a good ballpark estimate of the reservoir volume is a precursor to a good calibration.

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Section: Introductionmentioning

confidence: 99%

Data-driven modelling with coarse-grid network models

Lie

Krogstad

2023

Comput Geosci

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Parent–Child Well Spacing Optimization in Deep Shale Gas Reservoir with Two Complex Natural Fracture Patterns: A Sichuan Basin Case Study

Pei

Wu²,

Chang³

et al. 2022

Transp Porous Med

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Development of coupled fluid-flow/geomechanics model considering storage and transport mechanism in shale gas reservoirs with complex fracture morphology

Zhang,

Wu,

Jiang

et al. 2024

Sci Rep

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Field observations frequently demonstrate stress fluctuations resulting from the reservoir depletion. The development of reservoirs, particularly the completion of infill wells and refracturing, can be significantly impacted by stress changes in and around drainage areas. Previous studies mainly focus on plane fractures and few studies consider the influence of complex transport and storage mechanism and irregular fracture geometry on stress evolution in shale gas reservoirs. Based on the embedded discrete fracture model (EDFM) and finite-volume method (FVM), a coupled geomechanics/ fluid model has been successfully developed considering the adsorption, desorption, diffusion and slippage of shale gas. This model achieves coupling simulation of natural fractures, hydraulic fractures with complex geometry, storage and transport mechanism, reservoir stress, and pore-elastic effect. The open-source software OpenFOAM is used as the main solver for this model. The stress calculation and productivity simulation of the model are verified by the classical poroelasticity problem and the simulation results of published research and commercial simulator with EDFM respectively. The simulation results indicate that σ xx , σ yy , σ xy and Δσ changes with time and space due to the time effect and anisotropy of formation pressure depletion; Due to the influence of different mechanisms on shale gas storage and transport, the reservoir pressure and stress distribution under different mechanisms are different; Among them, the stress with full mechanisms differs the most compared to the stress without any mechanism. The reservoir with stronger stress sensitivity (smaller Biot coefficient) is less sensitive to formation pressure depletion, and the stress variation range is smaller. For reservoirs with weak stress sensitivity, formation pressure depletion is more likely to lead to stress reversal. Under the influence of fracture geometry, the pressure depletion regions caused by the three types of fracture geometry are approximately rectangular, parallelogram and square, respectively. The corresponding σ xx , σ yy and Δσ also have great differences in spatial distribution and values. Therefore, the time effect, shale gas storage and transport mechanism and the influence of complex fracture geometry should be considered when predicting pressure depletion induced stress under the condition of simultaneous production. This study is of great significance for understanding the evolution law of stress induced by pressure consumption, as well as the design of infill wells and repeated fracturing.

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Middle East Steamflood Field Optimization Demonstration Project

Cited by 10 publications

References 7 publications

Data-driven modelling with coarse-grid network models

Data-driven modelling with coarse-grid network models

Parent–Child Well Spacing Optimization in Deep Shale Gas Reservoir with Two Complex Natural Fracture Patterns: A Sichuan Basin Case Study

Development of coupled fluid-flow/geomechanics model considering storage and transport mechanism in shale gas reservoirs with complex fracture morphology

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