scholarly journals Integrated fracture characterization of Asmari reservoir in Haftkel field

2022 ◽  
Author(s):  
Kourosh Khadivi ◽  
Mojtaba Alinaghi ◽  
Saeed Dehghani ◽  
Mehrbod Soltani ◽  
Hamed Hassani ◽  
...  
Keyword(s):  
Fractured Reservoirs ◽  
Numerical Algorithms ◽  
Fracture Network ◽  
Naturally Fractured Reservoirs ◽  
Development Plan ◽  
Production Data ◽  
Efficient Manner ◽  
Fracture Characterization ◽  
Future Production ◽  
Fracture Modeling

AbstractThe Asmari reservoir in Haftkel field is one of the most prolific naturally fractured reservoirs in the Zagros folded zone in the southwest of Iran. The primary production was commenced in 1928 and continued until 1976 with a plateau rate of 200,000 bbl/day for several years. There was an initial gas cap on the oil column. Gas injection was commenced in June 1976 and so far, 28% of the initial oil in place have been recovered. As far as we concerned, fracture network is a key factor in sustaining oil production; therefore, it needs to be characterized and results be deployed in designing new wells to sustain future production. Multidisciplinary fracture evaluation from well to reservoir scale is a great privilege to improve model’s accuracy as well as enhancing reliability of future development plan in an efficient manner. Fracture identification and modeling usually establish at well scale and translate to reservoir using analytical or numerical algorithms with the limited tie-points between wells. Evaluating fracture network from production data can significantly improve conventional workflow where limited inter-well information is available. By incorporating those evidences, the fracture modeling workflow can be optimized further where lateral and vertical connectivity is a concern. This paper begins with the fracture characterization whereby all available data are evaluated to determine fracture patterns and extension of fracture network across the field. As results, a consistent correlation is obtained between the temperature gradient and productivity of wells, also convection phenomenon is confirmed. The findings of this section help us in better understanding fracture network, hydrodynamic communication and variation of temperature. Fracture modeling is the next step where characteristics of fractures are determined according to the structural geology and stress directions. Also, the fault’s related fractures and density of fractures are determined. Meanwhile, the results of data evaluation are deployed into the fracture model to control distribution and characteristics of fracture network, thereby a better representation is obtained that can be used for evaluating production data and optimizing development plan.

A FRACTAL DISCRETE FRACTURE NETWORK MODEL FOR HISTORY MATCHING OF NATURALLY FRACTURED RESERVOIRS

Fractals ◽  
2019 ◽  
Vol 27 (01) ◽  
pp. 1940008 ◽  
Author(s):  
LIMING ZHANG ◽  
CHENYU CUI ◽  
XIAOPENG MA ◽  
ZHIXUE SUN ◽  
FAN LIU ◽  
...  
Keyword(s):  
History Matching ◽  
Fractured Reservoirs ◽  
Fracture Network ◽  
Naturally Fractured Reservoirs ◽  
Production Data ◽  
Multi Scale ◽  
Complex Fracture ◽  
Discrete Fracture ◽  
Dfn Model ◽  
Dimensional Optimization

The distribution of fractures is highly uncertain in naturally fractured reservoirs (NFRs) and may be predicted by using the assisted-history-matching (AHM) that calibrates the reservoir model according to some high-quality static data combined with dynamic production data. A general AHM approach for NFRs is to construct a discrete fracture network (DFN) model and estimate model parameters given the observations. However, the large number of fractures prediction required in the AHM process could pose a high-dimensional optimization problem. This difficulty is particularly challenging when the fractures form a complex multi-scale fracture network. We present in this paper an integrated AHM approach of NFRs to tackle these challenges. Two essential ingredients of the method are (1) a 2D fractal-DFN model constructed as the geological simulation model to describe the complex fracture network, and (2) a mixture of multi-scale parameters, built according to the fractal-DNF model, as an inversion parameter model to alleviate the high-dimensional optimization burden caused by complex fracture networks. A reservoir with a multi-scale fracture network is set up to test the performance of the proposed method. Numerical results demonstrate that by use of the proposed method, the fractures well recognized by assimilating production data.

A Sensitivity Analysis for Effective Parameters on 2D Fracture-Network Permeability

2009 ◽  
Vol 12 (03) ◽  
pp. 455-469 ◽  
Author(s):  
Alireza Jafari ◽  
Tayfun Babadagli
Keyword(s):  
Sensitivity Analysis ◽  
Experimental Design ◽  
Fractured Reservoirs ◽  
Fracture Network ◽  
Static Model ◽  
Naturally Fractured Reservoirs ◽  
Single Fracture ◽  
Data Sets ◽  
Fracture Networks ◽  
Fractal Characteristics

Summary Fracture-network mapping and estimation of its permeability constitute two major steps in static-model preparation of naturally fractured reservoirs. Although several different analytical methods were proposed in the past for calculating fracture-network permeability (FNP), different approaches are still needed for practical use. We propose a new and practical approach to estimate FNP using statistical and fractal characteristics of fracture networks. We also provide a detailed sensitivity analysis to determine the relative importance of fracture-network parameters on the FNP in comparison to single-fracture conductivity using an experimental-design approach. The FNP is controlled by many different fracture-network parameters such as fracture length, density, orientation, aperture, and single-fracture connectivity. Five different 2D fracture data sets were generated for random and systematic orientations. In each data set, 20 different combinations of fracture density and length for different orientations were tested. For each combination, 10 different realizations were generated. The length was considered as constant and variable. This yielded a total of 1,000 trials. The FNPs were computed through a commercial discrete-fracture-network (DFN) modeling simulator for all cases. Then, we correlated different statistical and fractal characteristics of the networks to the measured FNPs using multivariable-regression analysis. Twelve fractal (sandbox, box counting, and scanline fractal dimensions) and statistical (average length, density, orientation, and connectivity index) parameters were tested against the measured FNP for synthetically generated fracture networks for a wide range of fracture properties. All cases were above the percolation threshold to obtain a percolating network, and the matrix effect was neglected. The correlation obtained through this analysis using four data sets was tested on the fifth one with known permeability for verification. High-quality match was obtained. Finally, we adopted an experimental-design approach to identify the most-critical parameters on the FNP for different fracture-network types. The results are presented as Pareto charts. It is believed that the new method and results presented in this paper will be useful for practitioners in static-model development of naturally fractured reservoirs and will shed light on further studies on modeling and understanding the transmissibility characteristics of fracture networks. It should be emphasized that this study was conducted on 2D fracture networks and could be extended to 3D models. This, however, requires further algorithm development to use 2D fractal characteristics for 3D systems and/or development of fractal measurement techniques for a 3D system. This study will provide a guideline for this type of research.

scholarly journals New algorithm to simulate fracture network propagation using stationary and moving coordinates in naturally fractured reservoirs

2020 ◽  
Vol 8 (11) ◽  
pp. 4025-4042
Author(s):  
Zhiqiang Li ◽  
Zhilin Qi ◽  
Wende Yan ◽  
Xiaoliang Huang ◽  
Qianhua Xiao ◽  
...  
Keyword(s):  
Fractured Reservoirs ◽  
Fracture Network ◽  
Naturally Fractured Reservoirs ◽  
Naturally Fractured ◽  
Network Propagation

scholarly journals Predictive Modelling of Naturally Fractured Reservoirs Using Geomechanics and Flow Simulation

GeoArabia ◽  
2001 ◽  
Vol 6 (1) ◽  
pp. 27-42
Author(s):  
Stephen J. Bourne ◽  
Lex Rijkels ◽  
Ben J. Stephenson ◽  
Emanuel J.M. Willemse
Keyword(s):  
Fractured Reservoirs ◽  
Flow Simulation ◽  
Naturally Fractured Reservoirs ◽  
Natural Fracture ◽  
Production Data ◽  
Well Test ◽  
Fracture Networks ◽  
Field Scale ◽  
Fracture Permeability ◽  
Naturally Fractured

ABSTRACT To optimise recovery in naturally fractured reservoirs, the field-scale distribution of fracture properties must be understood and quantified. We present a method to systematically predict the spatial distribution of natural fractures related to faulting and their effect on flow simulations. This approach yields field-scale models for the geometry and permeability of connected fracture networks. These are calibrated by geological, well test and field production data to constrain the distributions of fractures within the inter-well space. First, we calculate the stress distribution at the time of fracturing using the present-day structural reservoir geometry. This calculation is based on a geomechanical model of rock deformation that represents faults as frictionless surfaces within an isotropic homogeneous linear elastic medium. Second, the calculated stress field is used to govern the simulated growth of fracture networks. Finally, the fractures are upscaled dynamically by simulating flow through the discrete fracture network per grid block, enabling field-scale multi-phase reservoir simulation. Uncertainties associated with these predictions are considerably reduced as the model is constrained and validated by seismic, borehole, well test and production data. This approach is able to predict physically and geologically realistic fracture networks. Its successful application to outcrops and reservoirs demonstrates that there is a high degree of predictability in the properties of natural fracture networks. In cases of limited data, field-wide heterogeneity in fracture permeability can be modelled without the need for field-wide well coverage.

Multiscale-Network Structure Inversion of Fractured Media Based on a Hierarchical-Parameterization and Data-Driven Evolutionary-Optimization Method

SPE Journal ◽  
2020 ◽  
Vol 25 (05) ◽  
pp. 2729-2748
Author(s):  
Xiaopeng Ma ◽  
Kai Zhang ◽  
Chuanjin Yao ◽  
Liming Zhang ◽  
Jian Wang ◽  
...  
Keyword(s):  
Network Structure ◽  
Inverse Modeling ◽  
History Matching ◽  
Fractured Reservoirs ◽  
Fracture Network ◽  
Fractured Media ◽  
Naturally Fractured Reservoirs ◽  
Data Driven ◽  
Model Parameters ◽  
Parameterization Method

Summary Efficient identification and characterization of fracture networks are crucial for the exploitation of fractured media such as naturally fractured reservoirs. Using the information obtained from borehole logs, core images, and outcrops, fracture geometries can be roughly estimated. However, this estimation always has uncertainty, which can be decreased using inverse modeling. Following the Bayes framework, a common practice for inverse modeling is to sample from the posterior distribution of uncertain parameters, given the observational data. However, a challenge for fractured reservoirs is that the fractures often occur on different scales, and these fractures form an irregular network structure that is difficult to model and predict. In this work, a multiscale-parameterization method is developed to model the fracture network. Based on this parameterization method, we present a novel history-matching approach using a data-driven evolutionary algorithm to explore the Bayesian posterior space and decrease the uncertainties of the model parameters. Empirical studies on hypothetical and outcrop-based cases demonstrate that the proposed method can model and estimate the complex multiscale-fracture network on a limited computational budget.

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