Transient drainage volume characterization and flow simulation in reservoir models using the fast marching method

Author(s):  
Chen Li ◽  
Zhenzhen Wang ◽  
Michael J. King
SPE Journal ◽  
2019 ◽  
Vol 24 (06) ◽  
pp. 2590-2608 ◽  
Author(s):  
Xu Xue ◽  
Changdong Yang ◽  
Tsubasa Onishi ◽  
Michael J. King ◽  
Akhil Datta–Gupta

Summary Recently, fast–marching–method (FMM) –based flow simulation has shown great promise for rapid modeling of unconventional oil and gas reservoirs. Currently, the application of FMM–based simulation has been limited to using tartan grids to model the hydraulic fractures (HFs). The use of tartan grids adversely impacts the computational efficiency, particularly for field–scale applications with hundreds of HFs. Our purpose in this paper is to extend FMM–based simulation to incorporate local grid refinements (LGRs) and an embedded discrete fracture model (EDFM) to simulate HFs with natural fractures, and to validate the accuracy and efficiency of the methodologies. The FMM–based simulation is extended to LGRs and EDFM. This requires novel gridding through the introduction of triangles (2D) and tetrahedrons (2.5D) to link the local and global domain and solution of the Eikonal equation in unstructured grids to compute the diffusive time of flight (DTOF). The FMM–based flow simulation reduces a 3D simulation to an equivalent 1D simulation using the DTOF as a spatial coordinate. The 1D simulation can be carried out using a standard finite–difference method, thus leading to orders of magnitude of savings in computation time compared with full 3D simulation for high–resolution models. First, we validate the accuracy and computational efficiency of the FMM–based simulation with LGRs by comparing them with tartan grids. The results show good agreement and the FMM–based simulation with LGRs shows significant improvement in computational efficiency. Then, we apply the FMM–based simulation with LGRs to the case of a multistage–hydraulic–fractured horizontal well with multiphase flow, to demonstrate the practical feasibility of our proposed approach. After that, we investigate various discretization schemes for the transition between the local and global domain in the FMM–based flow simulation. The results are used to identify optimal gridding schemes to maintain accuracy while improving computational efficiency. Finally, we demonstrate the workflow of the FMM–based simulation with EDFM, including grid generation; comparison with FMM with unstructured grid; and validation of the results. The FMM with EDFM can simulate arbitrary fracture patterns without simplification and shows good accuracy and efficiency. This is the first study to apply the FMM–based flow simulation with LGRs and EDFM. The three main contributions of the proposed methodology are (i) unique mesh–generation schemes to link fracture and matrix flow domains, (ii) DTOF calculations in locally refined grids, and (iii) sensitivity studies to identify optimal discretization schemes for the FMM–based simulation.


SPE Journal ◽  
2014 ◽  
Vol 19 (06) ◽  
pp. 1069-1082 ◽  
Author(s):  
Mohammad Sharifi ◽  
Mohan Kelkar ◽  
Asnul Bahar ◽  
Tormod Slettebo

Summary One of the great challenges in reservoir modeling is to understand and quantify the dynamic uncertainties in geocellular models. Uncertainties in static parameters are easy to identify in geocellular models. Unfortunately, those models contain at least one to two orders of magnitude more gridblocks than typical simulation models. This means that, without significant upscaling, the dynamic uncertainties in these models cannot easily be assessed. Further, if we would like to select only a few geological models that can be carried forward for future performance predictions, we do not have an objective method of selecting the models that can properly capture the dynamic-uncertainty range. One possible solution is to use a faster simulation technique, such as streamline simulation. However, even streamline simulation requires solving a pressure equation at least once. For highly heterogeneous reservoir models with multimillion cells and in the presence of capillary effects or an expansion-dominated process, this can pose a challenge. If we use static permeability thresholds to determine the connected volume, it would not account for how tortuous the connection is between the connected gridblock and the well location. In this paper, we use the fast-marching method (FMM) as a computationally efficient method for calculating the pressure/front propagation time on the basis of reservoir properties. This method is based on solving the Eikonal equation by use of upwind finite-difference approximation. In this method, pressure/front location (radius of investigation) can be calculated as a function of time without running any flow simulation. We demonstrate that dynamically connected volume based on pressure-propagation time is a very good proxy for ultimate recovery from a well in the primary-depletion process. With a predetermined threshold propagation time, a large number of geocellular models can be ranked. FMM can be scaled almost linearly with the number of gridblocks in the model. Two main advantages of this ranking method compared with other methods are that this method determines dynamic connectivity in the reservoir and that it is computationally much more efficient. We demonstrate the validity of the method by comparing ranking of multiple geocellular realizations (on Cartesian grid with heterogeneous and anisotropic permeability) by use of FMM with ranking from flow simulation. This method will allow us to select the geological models that can truly capture the range of dynamic uncertainty very efficiently.


SPE Journal ◽  
2014 ◽  
Vol 20 (02) ◽  
pp. 347-359 ◽  
Author(s):  
Jiang Xie ◽  
Changdong Yang ◽  
Neha Gupta ◽  
Michael J. King ◽  
Akhil Datta-Gupta

Summary We present a novel approach to calculate drainage volume and well performance in shale gas reservoirs by use of the fast marching method (FMM) combined with a geometric pressure approximation. Our approach can fully account for complex fracture-network geometries associated with multistage hydraulic fractures and their impact on the well pressure and rates. The major advantages of our proposed approach are its simplicity, intuitive appeal, and computational efficiency. For example, we can compute and visualize the time evolution of the well-drainage volume for multimillion-cell geologic models in seconds without resorting to reservoir simulation. A geometric approximation of the drainage volume is then used to compute the well rates and the reservoir pressure. The speed and versatility of our proposed approach make it ideally suited for parameter estimation by means of the inverse modeling of shale-gas performance data. We use experimental design to perform the sensitivity analysis to identify the “heavy hitters” and a genetic algorithm (GA) to calibrate the relevant fracture and matrix parameters in shale-gas reservoirs by history matching of production data. In addition to the production data, microseismic information is used to help us constrain the fracture extent and orientation and to estimate the stimulated reservoir volume (SRV). The proposed approach is applied to a fractured shale-gas well. The results clearly show reduced ranges in the estimated fracture parameters and SRV, leading to improved forecasting and reserves estimation.


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.


2017 ◽  
Vol 149 ◽  
pp. 707-719 ◽  
Author(s):  
Behzad Pouladi ◽  
Mohammad Sharifi ◽  
Mohammad Ahmadi ◽  
Mohan Kelkar

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