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
2002 ◽  
Author(s):  
Zhong He ◽  
Harshal Parikh ◽  
Akhil Datta-Gupta ◽  
Jorge Perez ◽  
Tai Pham

SPE Journal ◽  
2019 ◽  
Vol 25 (01) ◽  
pp. 347-368
Author(s):  
Krishna Nunna ◽  
Michael J. King

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.


Fluids ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 7 ◽  
Author(s):  
Ruud Weijermars ◽  
Aadi Khanal ◽  
Lihua Zuo

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.


SPE Journal ◽  
2016 ◽  
Vol 21 (06) ◽  
pp. 2276-2288 ◽  
Author(s):  
Yusuke Fujita ◽  
Akhil Datta-Gupta ◽  
Michael J. King

Summary Modeling of fluid flow in unconventional reservoirs requires accurate characterization of complex flow mechanisms because of the interactions between reservoir rock, microfractures, and hydraulic fractures. The pore-size distribution in shale and tight sand reservoirs typically ranges from nanometers to micrometers, resulting in ultralow permeabilities. In such extremely low-permeability reservoirs, desorption and diffusive processes play important roles in addition to heterogeneity-driven convective flows. For modeling shale and tight oil and gas reservoirs, we can compute the well-drainage volume efficiently with a fast marching method (FMM) and by introducing the concept of “diffusive time of flight” (DTOF). Our proposed simulation approach consists of two decoupled steps—drainage-volume calculation and numerical simulation with DTOF as a spatial coordinate. We first calculate the reservoir drainage volume and the DTOF with the FMM, and then the numerical simulation is conducted along the 1D DTOF coordinate. The approach is analogous to streamline modeling whereby a multidimensional simulation is decoupled to a series of 1D simulations resulting in substantial savings in computation time for high-resolution simulation. However, instead of a “convective time of flight” (CTOF), a DTOF is introduced to model the pressure-front propagation. For modeling physical processes, we propose triple continua whereby the reservoir is divided into three different domains: microscale pores (hydraulic fractures and microfractures), nanoscale pores (nanoporous networks), and organic matter. The hydraulic fractures/microfractures primarily contribute to the well production, and are affected by rock compaction. The nanoporous networks contain adsorbed gas molecules, and gas flows into fractures by convection and Knudsen diffusion processes. The organic matter acts as the source of gas. Our simulation approach enables high-resolution flow characterization of unconventional reservoirs because of its efficiency and versatility. We demonstrate the power and utility of our approach with synthetic and field examples.


2021 ◽  
Author(s):  
Kenta Nakajima ◽  
Michael King

Abstract Recent studies have shown the utility of the Fast Marching Method and the Diffusive Time of Flight for the rapid simulation and analysis of Unconventional reservoirs, where the time scale for pressure transients are long and field developments are dominated by single well performance. We show that similar fast simulation and multi-well modeling approaches can be developed utilizing the PSS pressure as a spatial coordinate, providing an extension to both Conventional and Unconventional reservoir analysis. We reformulate the multi-dimensional multi-phase flow equations using the PSS pressure drop as a spatial coordinate. Properties are obtained by coarsening and upscaling a fine scale 3D reservoir model, and are then used to obtain fast single well simulation models. We also develop new 1D solutions to the Eikonal equation that are aligned with the PSS discretization, which better represent superposition and finite sized boundary effects than the original 3D Eikonal equation. These solutions allow the use of superposition to extend the single well results to multiple wells. The new solutions to the Eikonal equation more accurately represent multi-fracture interference for a horizontal MTFW well, the effects of strong heterogeneity, and finite reservoir extent than those obtained by the Fast Marching Method. The new methodologies are validated against a series of increasingly heterogeneous synthetic examples, with vertical and horizontal wells. We find that the results are systematically more accurate than those based upon the Diffusive Time of Flight, especially as the wells are placed closer to the reservoir boundary or as heterogeneity increases. The approach is applied to the Brugge benchmark study. We consider the history matching stage of the study and utilize the multi-well fast modeling approach to determine the rank quality of the 100+ static realizations provided in the benchmark dataset against historical data. The multi-well calculation uses superposition to obtain a direct calculation of the interaction of the rates and pressures of the wells without the need to explicitly solve flow equations within the reservoir model. The ranked realizations are then compared against full field simulation to demonstrate the significant reduction in simulation cost and the corresponding ability to explore the subsurface uncertainty more extensively. We demonstrate two completely new methods for rapid reservoir analysis, based upon the use of the PSS pressure as a spatial coordinate. The first approach demonstrates the utility of rapid single well flow simulation, with improved accuracy compared to the use of the Diffusive Time of Flight. We are also able to reformulate and solve the Eikonal equation in these coordinates, giving a rapid analytic method of transient flow analysis for both single and multi-well modeling.


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