History Matching of Naturally Fractured Reservoirs Using Elastic Stress Simulation and Probability Perturbation Method

2005 ◽  
Author(s):  
Satomi Suzuki ◽  
Colin Daly ◽  
Jef Karel Caers ◽  
Dietmar Mueller
Keyword(s):  
Perturbation Method ◽  
History Matching ◽  
Elastic Stress ◽  
Fractured Reservoirs ◽  
Naturally Fractured Reservoirs ◽  
Naturally Fractured ◽  
Stress Simulation ◽  
Probability Perturbation Method

History Matching of Naturally Fractured Reservoirs Using Elastic Stress Simulation and Probability Perturbation Method

SPE Journal ◽  
2007 ◽  
Vol 12 (01) ◽  
pp. 118-129 ◽  
Author(s):  
Satomi Suzuki ◽  
Colin Daly ◽  
Jef Karel Caers ◽  
Dietmar Mueller
Keyword(s):  
Boundary Conditions ◽  
History Matching ◽  
Elastic Stress ◽  
Fractured Reservoirs ◽  
Naturally Fractured Reservoirs ◽  
Structural Deformation ◽  
Fracture Density ◽  
Well Test ◽  
Fracture Modeling ◽  
Stress Simulation

Summary The application of elastic stress simulation for fracture modeling provides a more realistic description of fracture distribution than conventional statistical and geostatistical techniques, allowing the integration of geomechanical data and models into reservoir characterization. The geomechanical prediction of the fracture distribution accounts for the propagation of fracture caused by stress perturbation associated with faults. However, the challenge lies in estimating the past remote stress conditions which induced structural deformation and fracturing, the limited applicability of the elasticity assumption, and the latent uncertainty in the structural geometry of faults. The integration of historical production data and well-test permeability into geomechanical fracture modeling is a practical way to reduce such uncertainty. We propose to combine geostatistical algorithms for history matching with geomechanical elastic simulation models for developing an integrated yet efficient fracture modeling tool. This paper presents an integrated approach to history matching of naturally fractured reservoirs which includes (1) fracture trend prediction through elastic stress simulation; (2) geostatistical population of fracture density based on a fracture trend model; (3) fracture permeability modeling integrating fracture density, matrix permeability and well-test permeability; and (4) numerical flow simulation and history matching. All of these implementations are incorporated into a single forward modeling process and iterated in the automatic history-matching scheme. To obtain a history match on a reservoir model, we jointly perturb the large-scale fracture trend and local-scale geostatistical fluctuations of fracture densities rather than perturbing permeability calibrated from fractures. This strategy enables us to preserve the geological/geomechanical consistency throughout the history-matching process. The geomechanically simulated fracture trend model is calibrated to both production data and the reservoir geological structure (faults and horizons) by searching for the optimum remote stress condition for elastic stress-field simulation. The latter is achieved by matching the actually observed structural deformation with the simulated one. The smaller-scale fluctuation of fracture density is simultaneously history matched through the probability perturbation method of Caers (Caers 2003; Hoffman and Caers 2005; Caers 2007). The methodology is presented on a synthetic reservoir application. Introduction The modeling of the density and pattern of fracture distributions can take different approaches depending on the origin and the type of fracture sets and on the ultimate reservoir engineering questions raised. In this paper, we focus on the modeling of shear fractures which are generated by structural deformation accompanied with fault slip. Recently, an application of the elastic stress simulation has been proposed for predicting the pattern of shear/tensile fractures or the pattern of secondary faults and shown promising results (Bourne and Willemse 2001; Maerten et al. 2002; Bourne et al. 2001). The elastic simulation numerically simulates the structural deformation of the reservoir by solving linear elasticity equations under given boundary conditions, and simultaneously calculates the corresponding stress/strain tensor fields (Bourne and Willemse 2001; Maerten et al. 2002; Bourne et al. 2001; Daly and Mueller 2004; Roxar FracPerm Reference Manual 2005). The boundary conditions consist of (1) location/geometry of fault surface, (2) stress conditions or displacement conditions on the fault surfaces, and (3) the remote loads applied to the structure at the time of structural deformation accompanied with fault slippage. First, satisfying boundary conditions and by minimizing strain energy, the linear elastic equations are solved to obtain a structural deformation field which is expressed by the displacement vector. Next, strain field is computed from the displacement gradient based on the definition of strain. Finally, under the assumption of elasticity, stress is calculated from strain by means of Hook's law.

Effect of DFN Upscaling on History Matching and Prediction of Naturally Fractured Reservoirs

2013 ◽  
Author(s):  
Mohamed Ahmed Elfeel ◽  
Sarim Jamal ◽  
Chukwuemeka Enemanna ◽  
Dan Arnold ◽  
Sebastian Geiger
Keyword(s):  
History Matching ◽  
Fractured Reservoirs ◽  
Naturally Fractured Reservoirs ◽  
Naturally Fractured

Pressure-Transient Tests and Flow Regimes in Fractured Reservoirs

2015 ◽  
Vol 18 (02) ◽  
pp. 187-204 ◽  
Author(s):  
Fikri Kuchuk ◽  
Denis Biryukov
Keyword(s):  
History Matching ◽  
Fractured Reservoirs ◽  
Flow Regimes ◽  
Naturally Fractured Reservoirs ◽  
Dual Porosity ◽  
Hydraulic Fractures ◽  
Fractured Reservoir ◽  
Pressure Transient ◽  
Matrix Block ◽  
Naturally Fractured

Summary Fractures are common features in many well-known reservoirs. Naturally fractured reservoirs include fractured igneous, metamorphic, and sedimentary rocks (matrix). Faults in many naturally fractured carbonate reservoirs often have high-permeability zones, and are connected to numerous fractures that have varying conductivities. Furthermore, in many naturally fractured reservoirs, faults and fractures can be discrete (rather than connected-network dual-porosity systems). In this paper, we investigate the pressure-transient behavior of continuously and discretely naturally fractured reservoirs with semianalytical solutions. These fractured reservoirs can contain periodically or arbitrarily distributed finite- and/or infinite-conductivity fractures with different lengths and orientations. Unlike the single-derivative shape of the Warren and Root (1963) model, fractured reservoirs exhibit diverse pressure behaviors as well as more than 10 flow regimes. There are seven important factors that dominate the pressure-transient test as well as flow-regime behaviors of fractured reservoirs: (1) fractures intersect the wellbore parallel to its axis, with a dipping angle of 90° (vertical fractures), including hydraulic fractures; (2) fractures intersect the wellbore with dipping angles from 0° to less than 90°; (3) fractures are in the vicinity of the wellbore; (4) fractures have extremely high or low fracture and fault conductivities; (5) fractures have various sizes and distributions; (6) fractures have high and low matrix block permeabilities; and (7) fractures are damaged (skin zone) as a result of drilling and completion operations and fluids. All flow regimes associated with these factors are shown for a number of continuously and discretely fractured reservoirs with different well and fracture configurations. For a few cases, these flow regimes were compared with those from the field data. We performed history matching of the pressure-transient data generated from our discretely and continuously fractured reservoir models with the Warren and Root (1963) dual-porosity-type models, and it is shown that they yield incorrect reservoir parameters.

scholarly journals Evaluation of an uncertainty reduction methodology based on Iterative Sensitivity Analysis (ISA) applied to naturally fractured reservoirs

2019 ◽  
Vol 74 ◽  
pp. 40 ◽  
Author(s):  
Luís Augusto Nagasaki Costa ◽  
Célio Maschio ◽  
Denis José Schiozer
Keyword(s):  
Sensitivity Analysis ◽  
History Matching ◽  
Flow Behavior ◽  
Fractured Reservoirs ◽  
Search Space ◽  
Naturally Fractured Reservoirs ◽  
Reservoir Modeling ◽  
Naturally Fractured ◽  
Geostatistical Techniques

History matching for naturally fractured reservoirs is challenging because of the complexity of flow behavior in the fracture-matrix combination. Calibrating these models in a history-matching procedure normally requires integration with geostatistical techniques (Big Loop, where the history matching is integrated to reservoir modeling) for proper model characterization. In problems involving complex reservoir models, it is common to apply techniques such as sensitivity analysis to evaluate and identify most influential attributes to focus the efforts on what most impact the response. Conventional Sensitivity Analysis (CSA), in which a subset of attributes is fixed at a unique value, may over-reduce the search space so that it might not be properly explored. An alternative is an Iterative Sensitivity Analysis (ISA), in which CSA is applied multiple times throughout the iterations. ISA follows three main steps: (a) CSA identifies Group i of influential attributes (i = 1, 2, 3, …, n); (b) reduce uncertainty of Group i, with other attributes with fixed values; and (c) return to step (a) and repeat the process. Conducting CSA multiple times allows the identification of influential attributes hidden by the high uncertainty of the most influential attributes. In this work, we assess three methods: Method 1 – ISA, Method 2 – CSA, and Method 3 – without sensitivity analysis, i.e., varying all uncertain attributes (larger searching space). Results showed that the number of simulation runs for Method 1 dropped 24% compared to Method 3 and 12% to Method 2 to reach a similar matching quality of acceptable models. In other words, Method 1 reached a similar quality of results with fewer simulations. Therefore, ISA can perform as good as CSA demanding fewer simulations. All three methods identified the same five most influential attributes of the initial 18. Even with many uncertain attributes, only a small percentage is responsible for most of the variability of responses. Also, their identification is essential for efficient history matching. For the case presented in this work, few fracture attributes were responsible for most of the variability of the responses.

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.

History matching of naturally fractured reservoirs based on the recovery curve method

2015 ◽  
Vol 126 ◽  
pp. 211-221 ◽  
Author(s):  
Mojtaba Ghaedi ◽  
Mohsen Masihi ◽  
Zoltán E. Heinemann ◽  
Mohammad Hossein Ghazanfari
Keyword(s):  
History Matching ◽  
Fractured Reservoirs ◽  
Naturally Fractured Reservoirs ◽  
Recovery Curve ◽  
Naturally Fractured ◽  
Curve Method
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