Optimization-Based Unstructured Meshing Algorithms for Simulation of Hydraulically and Naturally Fractured Reservoirs with Variable Distribution of Fracture Aperture, Spacing, Length and Strike

2014 ◽  
Author(s):  
Jianlei Sun ◽  
David Stuart Schechter
Keyword(s):  
Fractured Reservoirs ◽  
Naturally Fractured Reservoirs ◽  
Fracture Aperture ◽  
Variable Distribution ◽  
Naturally Fractured ◽  
Unstructured Meshing ◽  
Spacing Length

Optimization-Based Unstructured Meshing Algorithms for Simulation of Hydraulically and Naturally Fractured Reservoirs With Variable Distribution of Fracture Aperture, Spacing, Length, and Strike

2015 ◽  
Vol 18 (04) ◽  
pp. 463-480 ◽  
Author(s):  
Jianlei Sun ◽  
David Schechter
Keyword(s):  
Fractured Reservoirs ◽  
Naturally Fractured Reservoirs ◽  
Natural Fracture ◽  
Fracture Networks ◽  
Complex Fracture ◽  
Naturally Fractured ◽  
Unstructured Meshing ◽  
Domain Discretization ◽  
Aperture Distribution ◽  
Spacing Length

Summary Multistage hydraulically fractured wells are applied widely to produce unconventional resource plays. In naturally fractured reservoirs, hydraulic-fracture treatments may induce complex-fracture geometries that one cannot model accurately and efficiently with Cartesian and corner-point grid systems or standard dual-porosity approaches. The interaction of hydraulic and naturally occurring fractures almost certainly plays a role in ultimate well and reservoir performance. Current simulation models are unable to capture the complexity of this interaction. Generally speaking, our ability to detect and characterize fracture systems is far beyond our capability of modeling complex natural-fracture systems. To evaluate production performance in these complex settings with numerical simulation, fracture networks require advanced meshing and domain-discretization techniques. This paper investigates these issues by developing natural-fracture networks with fractal-based techniques. After a fracture network is developed, we demonstrate the feasibility of gridding complex natural-fracture behavior with optimization-based unstructured meshing algorithms. Then we can demonstrate that one can simulate natural-fracture complexities such as variable aperture, spacing, length, and strike. This new approach is a significant step beyond the current method of dual-porosity simulation that essentially negates the sophisticated level of fracture characterization pursued by many operators. We use currently established code for fractal discrete-fracture-network (FDFN) models to build realizations of naturally fractured reservoirs in terms of stochastic fracture networks. From outcrop, image-log, and core analysis, it is possible to extract fracture fractal parameters pertaining to aperture, spacing, and length distribution, including center distribution as well as a fracture strike. Then these parameters are used as input variables for the FDFN code to generate multiple realizations of fracture networks mimicking fracture clustering and randomly distributed natural fractures. After incorporating hydraulic fractures, complex-fracture networks are obtained for further reservoir-domain discretization. To discretize the complex-fracture networks, a new mesh-generation approach is developed to conform to nonorthogonal and low-angle intersections of extensively clustered discrete-fracture networks with nonuniform aperture distribution. Optimization algorithms are adopted to reduce highly skewed cells, and to ensure good mesh quality around fracture tips, intersections, and regions of extensive fracture clustering. Moreover, local grid refinement is implemented with a predefined distance function to control cell sizes and shapes around and far away from fractures. Natural-fracture spacing, length, strike, and aperture distribution are explicitly gridded, thus introducing a new simulation approach that is far superior to dual-porosity simulation. Finally, initial sensitivity studies are performed to demonstrate both the capability of the optimization-based unstructured meshing algorithms, and the effect of aforementioned natural-fracture parameters on well performance. This study demonstrates how to incorporate a fractal-based characterization approach into the current work flow for simulating unconventional reservoirs, and most importantly solves several issues such as nonorthogonal intersections, extensive clustering, and nonuniform aperture distribution associated with domain discretization with unstructured grids for complex-fracture networks. The proposed meshing techniques for complex fracture networks can be easily implemented in existing preprocessing, unstructured mesh generators. The sensitivity study and the simulation runs demonstrate the importance of fracture characterization as well as uncertainties associated with naturally fractured reservoirs on well-production performance.

scholarly journals A new methodology to reduce uncertainty of global attributes in naturally fractured reservoirs

2018 ◽  
Vol 73 ◽  
pp. 41 ◽  
Author(s):  
Luís Augusto Nagasaki Costa ◽  
Célio Maschio ◽  
Denis José Schiozer
Keyword(s):  
Sensitivity Analysis ◽  
History Matching ◽  
Fractured Reservoirs ◽  
Probabilistic Approach ◽  
Fracture Network ◽  
Naturally Fractured Reservoirs ◽  
Fracture Aperture ◽  
Practical Case ◽  
Fractured Reservoir ◽  
Naturally Fractured

Accurately characterizing fractures is complex. Several studies have proposed reducing uncertainty by incorporating fracture characterization into simulations, using a probabilistic approach, to maintain the geological consistency, of a range of models instead of a single matched model. We propose a new methodology, based on one of the steps of a general history-matching workflow, to reduce uncertainty of reservoir attributes in naturally fractured reservoirs. This methodology maintains geological consistency and can treat many reservoir attributes. To guarantee geological consistency, the geostatistical attributes (e.g., fracture aperture, length, and orientation) are used as parameters in the history matching. This allows us to control Discrete Fracture Network attributes, and systematically modify fractures. The iterative sensitivity analysis allows the inclusion of many (30 or more) uncertain attributes that might occur in a practical case. At each uncertainty reduction step, we use a sensitivity analysis to identify the most influential attributes to treat in each step. Working from the general history-matching workflow of Avansi et al. (2016), we adapted steps for use with our methodology, integrating the history matching with geostatistical modeling of fractures and other properties in a big loop approach. We applied our methodology to a synthetic case study of a naturally fractured reservoir, based on a real semi-synthetic carbonate field, offshore Brazil, to demonstrate the applicability in practical and complex cases. From the initial 18 uncertain attributes, we worked with only 5 and reduced the overall variability of the Objective Functions. Although the focus is on naturally fractured reservoirs, the proposed methodology can be applied to any type of reservoir.

Estimation of Fracture Porosity of Naturally Fractured Reservoirs With No Matrix Porosity Using Fractal Discrete Fracture Networks

2009 ◽  
Vol 12 (02) ◽  
pp. 232-242 ◽  
Author(s):  
Tae H. Kim ◽  
David S. Schechter
Keyword(s):  
Fractured Reservoirs ◽  
Fracture Network ◽  
Naturally Fractured Reservoirs ◽  
Fracture Aperture ◽  
Fracture Networks ◽  
Fracture Porosity ◽  
Fracture Systems ◽  
Discrete Fracture ◽  
Naturally Fractured ◽  
Matrix Porosity

Summary Matrix porosity is relatively easy to measure and estimate compared to fracture porosity. On the other hand, fracture porosity is highly heterogeneous and very difficult to measure and estimate. When matrix porosity of naturally fractured reservoirs (NFRs) is negligible, it is very important to know fracture porosity to evaluate reservoir performance. Because fracture porosity is highly uncertain, fractal discrete fracture network (FDFN) generation codes were developed to estimate fracture porosity. To reflect scale-dependent characteristics of fracture networks, fractal theories are adopted. FDFN modeling technique enables the systematic use of data obtained from image log and core analysis for estimating fracture porosity. As a result, each fracture has its own fracture aperture distribution, so that generated FDFN are similar to actual fracture systems. The results of this research will contribute to properly evaluating the fracture porosity of NFR where matrix porosity is negligible.

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