Detailed Characterization of a Fractured Limestone Formation by Use of Stochastic Inverse Approaches

Datta‐Gupta, Akhil; Vasco, D. W.; Long, Jane C.; D'Onfro, P. S.; Rizer, William D.

doi:10.2118/27744-pa

Cited by 36 publications

(14 citation statements)

References 16 publications

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“…Several models are available to analyze tracer results. [13][14][15][16][17][18][19] In this paper, we present some simple concepts to assess the applicability of gel treatments in naturally fractured reservoirs-in particular, when channeling occurs between injector-producer pairs.…”

Section: Available Characterization Methodsmentioning

confidence: 99%

Gel Treatments for Reducing Channeling in Naturally Fractured Reservoirs

Seright

Lee

1999

SPE Production &Amp; Facilities

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This paper considers some of the reservoir variables that affect the severity of channeling and the potential of gel treatments for reducing channeling through naturally fractured reservoirs. We performed extensive tracer and gel placement studies using two different simulators. We show that gel treatments have the greatest potential when the conductivities of fractures that are aligned with direct flow between an injector-producer pair are at least 10 times the conductivity of off-trend fractures. Gel treatments also have their greatest potential in reservoirs with moderate to large fracture spacing. Produced tracer concentrations from interwell tracer studies can help identify reservoirs that are predisposed to successful gel applications. Our simulation studies also show how tracer transit times can be used to estimate the conductivity of the most direct fracture. The effectiveness of gel treatments should be insensitive to fracture spacing for fractures that are aligned with the direct flow direction. The effectiveness of gel treatments increases with increased fracture spacing for fractures that are not aligned with the direct flow direction. Tracer Transit Times in a Single FractureDuring a unit-mobility displacement, the time required for a tracer to travel between an injector-producer pair often provides a useful characterization of a fractured reservoir. [10][11][12][13] Of course, the tracer transit time depends on a number of variables, including the pressure drop between the wells (⌬p), the distance between wells (L), the number, orientation, and conductivity (k f w f ) of the connecting fractures, and the viscosity of the fluid in the fractures ͑͒.

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Section: Available Characterization Methodsmentioning

confidence: 99%

Gel Treatments for Reducing Channeling in Naturally Fractured Reservoirs

Seright

Lee

1999

SPE Production &Amp; Facilities

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“…Such conditioning is particularly important for fractured reservoirs because only a small fraction of the fractures in the DFN model might carry bulk of the fluid flow. 4,5 Streamline models have shown great potential in integrating dynamic data into high resolution geologic models. [6][7][8][9][10] A unique feature of streamline models has been the ability to efficiently compute the sensitivity of the production data to reservoir parameters such as porosity and permeability.…”

Section: Literature Reviewmentioning

confidence: 99%

Streamline-Based Production Data Integration in Naturally Fractured Reservoirs

Al-Harbi

Cheng

et al. 2005

SPE Journal

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Streamline-based models have shown great potential in reconciling high resolution geologic models to production data. In this work we extend the streamline-based production data integration technique to naturally fractured reservoirs. We use a dualporosity streamline model for fracture flow simulation by treating the fracture and matrix as separate continua that are connected through a transfer function. Next, we analytically compute the sensitivities that define the relationship between the reservoir properties and the production response in fractured reservoirs. Finally, production data integration is carried out via the Generalized Travel Time inversion (GTT). We also apply the streamline-derived sensitivities in conjunction with a dual porosity finite difference simulator to combine the efficiency of the streamline approach with the versatility of the finite difference approach. This significantly broadens the applicability of the streamlinebased approach in terms of incorporating compressibility effects and complex physics.The number of reservoir parameters to be estimated is commonly orders of magnitude larger than the observation data, leading to non-uniqueness and uncertainty in reservoir parameter estimate. Such uncertainty is passed to reservoir response forecast which needs to be quantified in economic and operational risk analysis. In this work we sample parameter uncertainty using a new two-stage Markov Chain Monte Carlo (MCMC) that is very fast and overcomes much of its current limitations. The computational efficiency comes through a substantial increase in the acceptance rate during MCMC by using a fast linearized approximation to the flow simulation and the likelihood function, the critical link between the reservoir model and production data. The Gradual Deformation Method (GDM) provides a useful framework to preserve geologic structure. Current dynamic data integration methods using GDM are inefficient due to the use of numerical sensitivity calculations which limits the method to deforming two or three models at a time. In this work, we derived streamline-based analytical sensitivities for the GDM that can be obtained from a single simulation run for any number of basis models. The new Generalized Travel Time GDM (GTT-GDM) is highly efficient and achieved a performance close to regular GTT inversion while preserving the geologic structure.

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“…The past few years have seen significant developments in the area of such dynamic data integration through the use of inverse modeling. [1][2][3][4][5][6][7][8][9][10][11][12][13] Streamline models have shown great promise in this regard. [9][10][11][12][13] The key advantages of streamline-based production data integration are its computational efficiency as a "forward" model and analytic computations of sensitivities of the production response with respect to reservoir parameters.…”

Section: Introductionmentioning

confidence: 99%

Streamline-Based Production Data Integration With Gravity and Changing Field Conditions

2002

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Recently, streamline-based flow simulation models have offered significant potential in integrating dynamic data into highresolution reservoir models. A unique feature of the streamlinebased production data integration has been the concept of a traveltime match that is analogous to seismic tomography, allowing the use of efficient and proven techniques from geophysics. In this paper, we propose a generalized travel-time inversion method for production data integration that is particularly well-suited for large-scale field applications with gravity and changing conditions. Instead of matching the production data directly, we minimize a travel-time shift derived by maximizing a cross-correlation between the observed and computed production response at each well. There are several advantages of our proposed method. First, it is general and extremely computationally efficient. The traveltime sensitivities can be computed analytically with a single forward streamline simulation that can be much faster than a conventional reservoir simulator. Second, it is robust and the minimization is relatively insensitive to the choice of the initial model. Finally, it is field-proven because we utilize established techniques from geophysical inverse theory.We demonstrate the power and utility of our proposed method using synthetic and field examples. The synthetic examples include a large-scale 3D example with a quarter-million grid cells involving infill drilling and pattern conversions. The field example is from the Goldsmith San Andres Unit (GSAU) in West Texas and includes multiple patterns with 11 injectors and 31 producers. Starting with a reservoir model based on well-log and seismic data, we integrate water-cut history for 20 years in less than 2 hours on a PC.

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Detailed Characterization of a Fractured Limestone Formation by Use of Stochastic Inverse Approaches

Cited by 36 publications

References 16 publications

Gel Treatments for Reducing Channeling in Naturally Fractured Reservoirs

Gel Treatments for Reducing Channeling in Naturally Fractured Reservoirs

Streamline-Based Production Data Integration in Naturally Fractured Reservoirs

Streamline-Based Production Data Integration With Gravity and Changing Field Conditions

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