Well Performance and Completion Efficiency Assessment in the Delaware Basin using the Diffusive Time of Flight

2021 ◽  
Author(s):  
Jaeyoung Park ◽  
Yuxing Ben ◽  
Vivek Muralidharan
Keyword(s):  
Time Of Flight ◽  
Well Performance ◽  
Delaware Basin ◽  
Efficiency Assessment ◽  
Diffusive Time

Dynamic Diffuse-Source Upscaling in High-Contrast Systems

SPE Journal ◽  
2019 ◽  
Vol 25 (01) ◽  
pp. 347-368
Author(s):  
Krishna Nunna ◽  
Michael J. King
Keyword(s):  
Cell Volume ◽  
Transient Flow ◽  
Time Of Flight ◽  
Local Source ◽  
Low Permeability ◽  
High Contrast ◽  
Pressure Transient ◽  
Diffuse Source ◽  
Cell Pair ◽  
Diffusive Time

Summary Traditional upscaling methods are dependent on steady-state (SS) concepts of flow, whereas flow simulation itself is used for the calculation of pressure and saturation transients, which can be considered as a sequence of pseudosteady-state (PSS) solutions. In high-contrast or low-permeability systems, neither the SS nor the PSS limits need to be reached within each coarse-cell volume during a simulation timestep, introducing a potentially significant bias into an upscaling or downscaling calculation. We use an asymptotic pressure analysis for transient flow, dependent on the diffusive time of flight, to improve the resolution of these dynamic effects. We introduce a novel upscaling approach with two major differences from SS upscaling. First, we transition from SS- to PSS-flow solutions. This has been shown to provide identical results to SS upscaling in one dimension, but to have improved localization for upscaling in two and three dimensions. Specifically, there is no longer an explicit dependence upon global pressure boundary conditions. Development of this PSS upscaling approach has also required the introduction of a new transmissibility-weighted pressure-averaging definition instead of the pore-volume (PV) -weighted pressure average used for SS flow. The second difference is in using pressure-transient concepts to identify well-connected subvolumes within a coarse-cell volume. The local source/sink terms during the transient are no longer solely proportional to porosity, as in the PSS limit. Instead, these terms now include a spatial dependence obtained from the asymptotic transient pressure approximation. This dependence is especially important for high-contrast or low-permeability systems. The methodology we have developed is an application of the concepts of the diffusive time of flight and transient drainage volume to obtain source functions that capture both the early- and late-time limits of the transient-flow patterns. Diffuse-source (DS) functions are introduced within each fine cell of a coarse-cell pair, consistent with the transients and with a specified total flux between the coarse cells. The ratio of this flux to the averaged pressure drop is used to obtain the effective transmissibility between the cell pair. The application of pressure-transient concepts has allowed us to develop completely local upscaling and downscaling calculations. A characteristic time is determined for which a well-connected subvolume for each coarse-cell pair is sufficiently close to PSS. This enables us to distinguish between well-connected and weakly connected pay while upscaling. Unlike SS upscaling calculations, which explicitly impose flow on the boundaries of an upscaling region and implicitly couple the local problem to a global flow field, these calculations are completely local. The methodology is tested on SPE10 (Christie and Blunt 2001) with permeability variations over eight orders of magnitude, making it a high-contrast example. We also test the method on a low-net/gross onshore tight gas reservoir consisting of thin fluvial channels undergoing primary depletion. The comparisons of performance prediction with fine-scale numerical simulation and SS upscaling demonstrate the accuracy of the proposed approach. NOTE: Supplement available in Supporting Information section.

Qualitative well placement and drainage volume calculations based on diffusive time of flight

2010 ◽  
Vol 75 (1-2) ◽  
pp. 178-188 ◽  
Author(s):  
Seyyed Abolfazl Hosseini ◽  
Suksang Kang ◽  
Akhil Datta-Gupta
Keyword(s):  
Time Of Flight ◽  
Well Placement ◽  
Drainage Volume ◽  
Volume Calculations ◽  
Diffusive Time

Identifying Reservoir Compartmentalization and Flow Barriers From Primary Production Using Streamline Diffusive Time of Flight

2004 ◽  
Vol 7 (03) ◽  
pp. 238-247 ◽  
Author(s):  
Zhong He ◽  
Harshal Parikh ◽  
Akhil Datta-Gupta ◽  
Jorge Perez ◽  
Tai Pham
Keyword(s):  
Primary Production ◽  
Time Of Flight ◽  
Reservoir Compartmentalization ◽  
Diffusive Time

scholarly journals Fast Models of Hydrocarbon Migration Paths and Pressure Depletion Based on Complex Analysis Methods (CAM): Mini-Review and Verification

Fluids ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 7 ◽  
Author(s):  
Ruud Weijermars ◽  
Aadi Khanal ◽  
Lihua Zuo
Keyword(s):  
Complex Analysis ◽  
Time Of Flight ◽  
Hydrocarbon Migration ◽  
Field Development ◽  
Analysis Methods ◽  
Pressure Depletion ◽  
Order Of Magnitude ◽  
Shale Reservoirs ◽  
Drained Rock Volume ◽  
Diffusive Time

A recently developed code to model hydrocarbon migration and convective time of flight makes use of complex analysis methods (CAM) paired with Eulerian particle tracking. Because the method uses new algorithms that are uniquely developed by our research group, validation of the fast CAM solutions with independent methods is merited. Particle path solutions were compared with independent solutions methods (Eclipse). These prior and new benchmarks are briefly summarized here to further verify the results obtained with CAM codes. Pressure field solutions based on CAM are compared with independent embedded discrete fracture method (EDFM) solutions. The CAM method is particularly attractive because its grid-less nature offers fast computation times and unlimited resolution. The method is particularly well suited for solving a variety of practical field development problems. Examples are given for fast optimization of waterflood patterns. Another successful application area is the modeling of fluid withdrawal patterns in hydraulically fractured wells. Because no gridding is required, the CAM model can compute the evolution of the drained rock volume (DRV) for an unlimited (but finite) number of both hydraulic and natural fractures. Such computations of the DRV are based on the convective time of flight and show the fluid withdrawal zone in the reservoir. In contrast, pressure depletion models are based on the diffusive time of flight. In ultra-low permeability reservoirs, the pressure depletion zones do not correspond to the DRV, because the convective and diffusive displacement rates differ over an order of magnitude (diffusive time of flight being the fastest). Therefore, pressure depletion models vastly overestimate the drained volume in shale reservoirs, which is why fracture and well spacing decisions should be based on both pressure depletion and DRV models, not pressure only.

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