In-Situ Characterization of Residual NAPL Distribution Using Streamline-Based Inversion of Partitioning Tracer Tests

Yoon, Sungroh; Barman, Indranil; Datta‐Gupta, Akhil; Pope, Gary A.

doi:10.2118/52729-ms

Cited by 17 publications

(11 citation statements)

References 14 publications

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“…Yoon et al 12 demonstrated the utility of the streamline-based inversion method for estimating non-aqueous phase liquid (NAPL) saturation in an aquifer from PITT data and applied the method to a set of tracer tests carried out in a test cell at the Hill Airforce Base. In this paper we show how a field-scale PITT data can be analyzed using the streamline-based inverse method.…”

Section: Spe 71320mentioning

confidence: 99%

Field-Scale Characterization of Permeability and Saturation Distribution Using Partitioning Tracer Tests: The Ranger Field, Texas

Iliassov

Datta‐Gupta

Vasco

2001

SPE Annual Technical Conference and Exhibition

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper discusses the application of an efficient streamlinebased inversion method to a large multi-well multi-tracer Partitioning Interwell Tracer Test (PITT) in the McClesky sandstone, Ranger Field, Texas, to characterize both permeability and oil saturation distribution. During a typical PITT, a conservative and a partitioning tracer are injected into the reservoir. The partitioning tracer gets partially absorbed into the oil phase, leading to a separation in the tracer responses that can be used to infer oil saturation distribution in the tracer-swept area. Our approach is extremely efficient because it relies on analytic computation of the sensitivity of the tracer response to reservoir parameters such as permeability and saturation using a single streamline simulation. We follow a two step procedure whereby we first match the conservative tracer response to determine the permeability distribution and then match the partitioning tracer response to obtain oil saturation distribution in the reservoir. The entire history matching took less than 6 hours in a PC as opposed to several months typically required for a manual history matching.We compared our results to a manual history match obtained using a finite-difference simulator. Both the manual history matching and the streamline-based inversion identified similar large-scale trends in permeability and saturation distribution.However, well-specific matches were significantly improved over those obtained through the manual history matching. Our approach is much more efficient in terms of computation time and effort and the results are less sensitive to personal bias compared to manual history matching. Finally, we discuss a procedure to assess the results in terms of resolution of the estimates of permeability and saturation distribution.

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Section: Spe 71320mentioning

confidence: 99%

Field-Scale Characterization of Permeability and Saturation Distribution Using Partitioning Tracer Tests: The Ranger Field, Texas

Iliassov

Datta‐Gupta

Vasco

2001

SPE Annual Technical Conference and Exhibition

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“…More importantly, we can compute sensitivities of the production response to reservoir parameters analytically using a single forward simulation. 4,5,9,10 • Hierarchical Parameterization. Unknown reservoir properties are parameterized in a hierarchical fashion according to the data resolution.…”

Section: Approachmentioning

confidence: 99%

“…We have addressed these issues in detail in our previous publications. 4,10 Utilizing these features, we can effectively decouple the forward modeling and inversion to further increase the computational speed. Our approach involves decomposing the inverse problem by scale and integration of production data by a scale-by-scale inversion.…”

Section: Multiscale Inversion: Mathematical Formulationmentioning

confidence: 99%

A Multiscale Approach to Production Data Integration Using Streamline Models

Yoon

Malallah

Datta-Gupta

et al. 1999

Proceedings of SPE Annual Technical Conference and Exhibition

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractWe propose a multiscale approach to data integration that accounts for the varying resolving power of different data types from the very outset. Starting with a very coarse description, we match the production response at the wells by recursively refining the reservoir grid. A multiphase streamline simulator is utilized for modeling fluid flow in the reservoir. The well data is then integrated using conventional geostatistics, for example sequential simulation methods. There are several advantages to our proposed approach. First, we explicitly account for the resolution of the production response by refining the grid only up to a level sufficient to match the data, avoiding over-parameterization and incorporation of artificial regularization constraints. Second, production data is integrated at a coarse-scale with fewer parameters, which makes the method significantly faster compared to direct fine-scale inversion of the production data. Third, decomposition of the inverse problem by scale greatly facilitates the convergence of iterative descent techniques to the global solution, particularly in the presence of multiple local minima. Finally, the streamline approach allows for parameter sensitivities to be computed analytically using a single simulation run and thus, further enhancing the computational speed.The proposed approach has been applied to synthetic as well as field examples. The synthetic examples illustrate the validity of the approach and also address several key issues such as convergence of the algorithm, computational efficiency, and advantages of the multiscale approach compared to conventional methods. The field example is from the Goldsmith San Andres Unit (GSAU) in West Texas and includes multiple patterns consisting of 11 injectors and 31 producers. Using well log data and water-cut history from producing wells, we characterize the permeability distribution, thus demonstrating the feasibility of the proposed approach for large-scale field applications.

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“…Oil distribution between wells is derived by matching the tracer production profiles using a 3D finite difference simulator such as UTCHEM 6,7 or by a streamline model. 8,9 To circumvent the technical problems encountered in simulation, an analytical chromatographic transformation method was proposed by Tang 2-4 and Wood et al 5 and a moment-analysis method [10][11][12][13] to calculate S orw directly by comparing the relative separation of tracers. Chromatographic transformation was employed by and Wood et al 5 to determine S orw for the Golden Spike, Judy Creek, and Leduc interwell partitioning tracer tests.…”

Section: Introductionmentioning

confidence: 99%

Extended Brigham Model for Residual oil Saturation Measurement by Partitioning Tracer Tests

Tang

2005

SPE Journal

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Brigham's model has been used extensively in the petroleum industry for the design and interpretation of interwell tracer tests. The model is based on correlation and has included physical dispersion as an input parameter. In spite of its limitations, the model is useful in estimating layer heterogeneity, layer distribution, permeability contrast, and dispersion in the reservoir. However, the model can only handle nonpartitioning tracers that have no solubility in oil. With the advancement in partitioning tracer technology and interpretation technique, interwell partitioning tracer testing has gained its popularity, especially in China, 1 for determining residual oil saturation, S orw , between wells. Partitioning tracer testing also finds its application in environmental protection, where tests are routinely run to determine the amount of nonaqueous liquid phase nonaqueous phase liquid (NAPL) trapped underground due to spill or seepage. While sophisticated streamline or finite difference simulators have been increasingly used to determine S orw distribution from the tracer production data, the simple semiquantitative model still has its merits in providing a direct, unambiguous estimate of average S orw along the tracer flow path. This paper broadens the scope of the original Brigham's model by incorporating partitioning tracers into the model using a chromatographic transformation technique. By matching the partitioning and nonpartitioning tracer curves, S orw can be determined by layers. The extended Brigham model was applied to the Ranger oilfield multiple tracer test, and the residual oil saturation determined compared favorably with those obtained by chromatographic transformation method and numerical simulation.

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In-Situ Characterization of Residual NAPL Distribution Using Streamline-Based Inversion of Partitioning Tracer Tests

Cited by 17 publications

References 14 publications

Field-Scale Characterization of Permeability and Saturation Distribution Using Partitioning Tracer Tests: The Ranger Field, Texas

Field-Scale Characterization of Permeability and Saturation Distribution Using Partitioning Tracer Tests: The Ranger Field, Texas

A Multiscale Approach to Production Data Integration Using Streamline Models

Extended Brigham Model for Residual oil Saturation Measurement by Partitioning Tracer Tests

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