scholarly journals Fuzzy rock typing: Enhancing reservoir simulation and modeling by honoring high resolution geological models

2009 ◽  
Author(s):  
Vida Gholami
Keyword(s):  
High Resolution ◽  
Reservoir Simulation ◽  
Simulation And Modeling ◽  
Rock Typing ◽  
Geological Models

Rock Typing as an Effective Tool for Permeability and Water-Saturation Modeling: A Case Study in a Clastic Reservoir in the Oriente Basin

2007 ◽  
Vol 10 (06) ◽  
pp. 730-739 ◽  
Author(s):  
Genliang Guo ◽  
Marlon A. Diaz ◽  
Francisco Jose Paz ◽  
Joe Smalley ◽  
Eric A. Waninger
Keyword(s):  
Relative Permeability ◽  
Reservoir Simulation ◽  
Water Saturation ◽  
Rock Type ◽  
Permeability Model ◽  
Initial Water ◽  
Rock Types ◽  
Rock Typing ◽  
Relative Permeability Curves ◽  
Clastic Reservoirs

Summary In clastic reservoirs in the Oriente basin, South America, the rock-quality index (RQI) and flow-zone indicator (FZI) have proved to be effective techniques for rock-type classifications. It has long been recognized that excellent permeability/porosity relationships can be obtained once the conventional core data are grouped according to their rock types. Furthermore, it was also observed from this study that the capillary pressure curves, as well as the relative permeability curves, show close relationships with the defined rock types in the basin. These results lead us to believe that if the rock type is defined properly, then a realistic permeability model, a unique set of relative permeability curves, and a consistent J function can be developed for a given rock type. The primary purpose of this paper is to demonstrate the procedure for implementing this technique in our reservoir modeling. First, conventional core data were used to define the rock types for the cored intervals. The wireline log measurements at the cored depths were extracted, normalized, and subsequently analyzed together with the calculated rock types. A mathematical model was then built to predict the rock type in uncored intervals and in uncored wells. This allows the generation of a synthetic rock-type log for all wells with modern log suites. Geostatistical techniques can then be used to populate the rock type throughout a reservoir. After rock type and porosity are populated properly, the permeability can be estimated by use of the unique permeability/porosity relationship for a given rock type. The initial water saturation for a reservoir can be estimated subsequently by use of the corresponding rock-type, porosity, and permeability models as well as the rock-type-based J functions. We observed that a global permeability multiplier became unnecessary in our reservoir-simulation models when the permeability model is constructed with this technique. Consistent initial-water-saturation models (i.e., calculated and log-measured water saturations are in excellent agreement) can be obtained when the proper J function is used for a given rock type. As a result, the uncertainty associated with volumetric calculations is greatly reduced as a more accurate initial-water-saturation model is used. The true dynamic characteristics (i.e., the flow capacity) of the reservoir are captured in the reservoir-simulation model when a more reliable permeability model is used. Introduction Rock typing is a process of classifying reservoir rocks into distinct units, each of which was deposited under similar geological conditions and has undergone similar diagenetic alterations (Gunter et al. 1997). When properly classified, a given rock type is imprinted by a unique permeability/porosity relationship, capillary pressure profile (or J function), and set of relative permeability curves (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993). As a result, when properly applied, rock typing can lead to the accurate estimation of formation permeability in uncored intervals and in uncored wells; reliable generation of initial-water-saturation profile; and subsequently, the consistent and realistic simulation of reservoir dynamic behavior and production performance. Of the various quantitative rock-typing techniques (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993; Porras and Campos 2001; Jennings and Lucia 2001; Rincones et al. 2000; Soto et al. 2001) presented in the literature, two techniques (RQI/FZI and Winland's R35) appear to be used more widely than the others for clastic reservoirs (Gunter et al. 1997, Amaefule et al. 1993). In the RQI/FZI approach (Amaefule et al. 1993), rock types are classified with the following three equations: [equations]

High-Resolution Compositional Reservoir Simulation with Dynamic Coarsening and Local Timestepping for Unstructured Grids

SPE Journal ◽  
2021 ◽  
pp. 1-17
Author(s):  
Ø. S. Klemetsdal ◽  
O. Møyner ◽  
A. Moncorgé ◽  
H. M. Nilsen ◽  
K-. A. Lie
Keyword(s):  
High Resolution ◽  
Reservoir Simulation ◽  
Unstructured Grids ◽  
Computational Time ◽  
Flow Equations ◽  
Flow Models ◽  
Fluid Physics ◽  
Computational Overhead ◽  
Complex Fluid ◽  
Quantities Of Interest

Summary Numerical smearing is oftentimes a challenge in reservoir simulation, particularly for complex tertiary recovery strategies. We present a new high-resolution method that uses dynamic coarsening of a fine underlying grid in combination with local timestepping to provide resolution in time and space. The method can be applied to stratigraphic and general unstructured grids, is efficient, introduces minimal computational overhead, and is applicable to flow models seen in practical reservoir engineering. Technically, the method is based on three concepts: Sequential splitting of the flow equations into a pressure equation and a system of transport equations Dynamic coarsening in which we temporarily coarsen the grid locally by aggregating cells into coarse blocks according to cell-wise indicators on the basis of residuals (gradients and other measures of spatial and temporal changes can also be used) Asynchronous local timestepping that traverses cells/coarse blocks in the direction of flow We assess the applicability of the method through a set of representative cases, ranging from conceptual to realistic, with complex fluid physics and reservoir geology, and demonstrate that the method can be used to reduce computational time and still retain high resolution in spatial/temporal zones and quantities of interest.

Upscaling Technique for Highly Heterogeneous Reservoirs Based on Flow and Storage Capacity and the Lorenz Coefficient

SPE Journal ◽  
2020 ◽  
Vol 25 (04) ◽  
pp. 1981-1999 ◽  
Author(s):  
Victor S. Rios ◽  
Luiz O. S. Santos ◽  
Denis J. Schiozer
Keyword(s):  
Reservoir Simulation ◽  
Storage Capacity ◽  
Simulation Models ◽  
Scaling Up ◽  
Fine Scale ◽  
Coarse Scale ◽  
Heterogeneous Reservoirs ◽  
Upscaling Technique ◽  
Geological Models ◽  
And Storage

Summary Field-scale representation of highly heterogeneous reservoirs remains a challenge in numerical reservoir simulation. In such reservoirs, detailed geological models are important to properly represent key heterogeneities. However, high computational costs and long simulation run times make these detailed models unfeasible to use in dynamic evaluations. Therefore, the scaling up of geological models is a key step in reservoir-engineering studies to reduce computational time. Scaling up must be carefully performed to maintain integrity; both truncation errors and the smoothing of subgrid heterogeneities can cause significant errors. This work evaluates the latter—the effect of averaging small-scale heterogeneities in the upscaling process—and proposes a new upscaling technique to overcome the associated limitations. The technique is dependent on splitting the porous media into two levels guided by flow- and storage-capacity analysis and the Lorenz coefficient (LC), both calculated with static properties (permeability and porosity) from a fine-scale reference model. This technique allows the adaptation of a fine highly heterogeneous geological model to a coarse-scale simulation model in a dual-porosity/dual-permeability (DP/DP) approach and represents the main reservoir heterogeneities and possible preferential paths. The new upscaling technique is applied to different reservoir-simulation models with water injection and immiscible gas injection as recovery methods. In deterministic and probabilistic studies, we show that the resulting coarse-scale dual-permeability models are more accurate and can better reproduce the fine-scale results in different upscaling ratios (URs), without using any simulation results of the reference fine-scale simulation models, as some of the current alternative upscaling methods do.

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