Natural Fractured Reservoirs Characteristics Estimation Based on Production Data using Simplified Correlation. Examples from Russia (Russian)

2017 ◽  
Author(s):  
V Syrtlanov ◽  
E. Kovaleva ◽  
A. Aleev
Keyword(s):  
Fractured Reservoirs ◽  
Production Data ◽  
Characteristics Estimation

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.

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.

Sign in / Sign up

Export Citation Format

Share Document