The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
- Data Science & Engineering Analytics
The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
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Liu, Jinju (Petroleum Systems Engineering, Faculty of Engineering and Applied Science, University of Regina) | Jiang, Liwu (Petroleum Systems Engineering, Faculty of Engineering and Applied Science, University of Regina) | Liu, Tongjing (Unconventional Petroleum Research Institute, China University of Petroleum (Beijing)) | Yang, Daoyong (Petroleum Systems Engineering, Faculty of Engineering and Applied Science, University of Regina (Corresponding author))
Summary In a naturally fractured reservoir, natural fractures can not only provide main paths for fluid flow and increase its permeability but also complicate flow behavior and production performance. Interwell tracer tests have been widely applied to estimate the petrophysical properties; however, limited attempts have been made to accurately identify the natural fracture networks. In this study, the newly proposed numerical models have been verified and used to characterize the fracture distributions in a naturally fractured reservoir conditioned to tracer transport behavior. The stochastic fracture modeling approach is implemented to generate the randomly distributed natural fractures which are dealt with the embedded discrete fracture model (EDFM) while ensuring its sufficient accuracy. To be specific, the matrix domain is discretized using the structured grids, within which each embedded fracture is divided into a series of segments. Subsequently, nonneighboring connections (NNCs) allow us to couple the flow of fluid and tracer between the nonneighboring grid cells, while the historical tracer profiles are matched to delineate the geometry and properties of the fractures by taking multiple tracer transport mechanisms into account. Furthermore, the influences of fracture number, fracture length, fracture orientation, and tracer dispersion on the tracer production concentration have been investigated through sensitivity analysis. The response of an interwell tracer model is sensitive to the fracture parameters rather than tracer properties. A fracture network with its orientation parallel to the mainstream direction will cause the earliest tracer breakthrough. The tracer breakthrough time with an average fracture length of 40 m is 110 days earlier than that with a mean fracture length value of 10 m, while the tracer production peak concentration for the former is nearly two times higher than for the latter. A larger fracture number results in an earlier tracer breakthrough, and an intermediate fracture number will lead to the highest tracer production concentration. Additionally, the newly developed model has been validated through its comparison with the commercial ECLIPSE simulator and then extended to field applications to identify the possible fracture distributions by simulating multiwell tracer tests in the Midale field. The flexible and pragmatic EDFM-based method developed in this study can model the interwell tracer flow behavior as well as characterize the properties and geometries of the natural fractures with better accuracy and calculation efficiency in comparison with other fracture simulation methods (e.g., local grid refinement method).
Abstract Modeling complex transport processes in naturally fractured reservoirs (NFRs) using classical continuum models may not be practically possible, because using classical algorithms for the detailed structure of fracture-matrix system requires unreasonable computational time. Also, fractured reservoirs are highly heterogeneous, and finite-difference calculations for such models often cause convergence problems. In addition to these, an exact representation of a complex fracture network in classical continuum modeling algorithms is highly difficult. An alternative is to use a non-classical technique known as the Random Walk Particle Tracking (RWPT) algorithm. We showed earlier (Stalgorova and Babadagli, 2009) that the random walk (RW) technique can be adapted to model miscible flooding in a fractured porous medium at the lab scale. The unknown parameters used to match the model results were only diffusion coefficients for oil and solvent, as the diffusive/dispersive transport (effective if fracture and matrix) was coupled with viscous (effective in fracture) and gravity (effective in fracture and matrix) displacement. Advantages of this method over classical simulation are: (1) shorter computational time, which allows avoidance of simplifications, and (2) the ability to model the matrix-fracture diffusion process without any transfer function. In the present paper, we modified this lab scale RW model for field scale applications. For validation, a series of tracer test results from the Midale field in Canada was used. Fracture network model was constructed based on geological data, and then we used the RWPT model to calibrate the fracture network against tracer test results. We performed a sensitivity analysis to identify the importance of different parameters for the simulation results. The new model and observations can be used to validate and calibrate stochastically generated fracture network models and to estimate the EOR performance of NFRs.
Summary Modeling complex transport processes in naturally fractured reservoirs (NFRs) using classical continuum models may not be practically possible because the algorithms used in this type of modeling approach for the detailed structure of fracture/matrix systems require unreasonable computational time. Also, fractured reservoirs are highly irregular, and finite-difference calculations for such models often cause convergence problems. In addition, an exact representation of a complex fracture network in classical continuum modeling algorithms is highly difficult. An alternative is to use a nonclassical technique known as the random-walk particle-tracking (RWPT) algorithm. We showed earlier (Stalgorova and Babadagli 2012) that the random-walk (RW) technique can be adapted to model miscible flooding in a fractured porous medium at the laboratory scale. The unknown parameters used to match the model results were only the diffusion coefficients for oil and solvent, as the diffusive/dispersive transport (effective in fracture and matrix) was coupled with viscous (effective in fracture) and gravity (effective in fracture and matrix) displacement. Advantages of this method over classical simulation include a shorter computational time, which allows avoidance of simplifications; the ability to model the matrix/fracture diffusion process without any transfer function; and the representation of a complex and irregular fracture network system. In this paper, we modified this laboratory-scale RW model for field-scale applications. A series of tracer-test results from the Midale field in Canada was used to test the model. A fracture-network model was constructed on the basis of geological data, and then we used the RWPT model to calibrate the fracture network against tracer-test results. The results were compared to those obtained using continuum (dual-porosity) models, and it was observed that the connectivity and breakthrough times can be captured more correctly with the RWPT model. We performed a sensitivity analysis to identify the importance of different parameters for the simulation results. The new model and observations can be used to validate and calibrate stochastically generated fracture-network models and to estimate the enhanced-oil-recovery (EOR) performance of NFRs.
Wu, Qianhui (China University of Petroleum East China) | Ge, Jijiang (China University of Petroleum East China) | Ding, Lei (Texas A&M University at Qatar) | Wei, Kaipeng (Sinopec North China Petroleum Bureau, Zhengzhou) | Liu, Yuelong (Sinopec North China Petroleum Bureau, Zhengzhou) | Deng, Xuefeng (Sinopec North China Petroleum Bureau, Zhengzhou)
Abstract The wide existence of fractures makes conformance control by polymer gels more challenging in water-flooded oil reservoirs. Selection of an applicable gel system and design of an intelligent approach for gel treatment are key components for a successful field application. Moreover, selecting the candidate wells and determining the injection volume of gel are also critical to the success of gel treatments. A gel system with adjustable polymer concentrations was applied for conformance control in fractured tight sandstone reservoir, and notably, less than 5% of syneresis was detected after aging for one year at reservoir condition. The viscosity and the gelation time of this gel system can be adjusted according to the targeted reservoir conditions. The pilot test was conducted in Huabei oilfield (China), and the oil recovery after water flooding was only about 20% original oil in place (OOIP). With further exploitation of the oil field, the majority of the reservoir has suffered from poor sweep efficiency and extremely high water cuts. To characterize the distribution of fractures, the seismic coherence cube was utilized. In addition, the pressure transient test, interwell tracer test and the injection-production data were used collaboratively to determine the volume of fractures in the reservoir. The option of gel formulation and the determination of operational parameters are mainly based on the wellhead pressure. According to the seismic coherence cube, the zone of candidate well group shows a weak coherence state, indicating that numerous fractures exist. Furthermore, there is good continuity between the candidate injection well and the production well. According to the pressure transient test, the volume of re-open fracture is about 1730.9 m, while the volume of micro-fracture is about 4839.4 m. Comparably, based on the interwell tracer test, the estimated volume of fractures is approximately 3219.7 m. Consequently, the designed volume of gel for treatment is 1500.0 m in total. The properties of gel slugs were carefully designed, which was tailored to the specific wellbore conditions and formation characteristics. Three months after the gel treatment, the average oil production was increased from 0.36 t/d to 0.9 t/d, and the water cut was decreased from 95.77% to 88.7%. The improved oil production was still benefited from this gel treatment after one year. This study provides a comprehensive approach, from optimization of gel formulation, followed by selection of candidate wells, to calculation of the injected volume, to design the viable operational parameters, for gel treatment field application in fractured reservoirs. It shows that, besides a gel system with superior properties, a suitable injected volume of gel may enhance the chance of success for gel treatments.
Summary We used an integrated solution by combining "direct" and "inverse" approaches to fracture network characterization in a stochastic numerical model. Static geological data obtained from cores and well logs were used together with dynamic data such as well-test responses to build 3D discrete fracture-network models. We used the data obtained from the fractured carbonate Midale field in Canada. The fractured-reservoir model was constructed from static and dynamic (drawdown and pulse-interference tests) data. Matrix and several fracture parameters including fracture length, density/spacing, aperture, connectivity, and orientation were evaluated in a quantitative sensitivity study to determine which characteristics have a higher influence on the accurate match to well-test response. We used experimental design to optimize the number of simulations needed for a sensitivity study and history match. The sensitivity analysis revealed a strong influence of matrix quality on the pressure response, suggesting that the history match can be specific to the simulated process and not necessarily unique. The results emphasize the contribution of matrix in the Midale reservoir and the need to simulate a broader range of processes for an accurate description of the fracture/matrix system dynamics. In a general sense, the approach used in this study proved to be useful in integrating fracture data from different sources and assessing its reliability and relative importance. Introduction In this study, we apply a widely accepted integrated approach to characterize the matrix/fracture system of the Midale field in southeastern Saskatchewan, Canada. Often serving as an example for classical NFR in literature, Midale is a perfect case study for several reasons. The field produces light oil from a mature carbonate reservoir. Currently Midale is undergoing a full-field CO2 flooding, which became possible largely thanks to the success of the pilot CO2 flood project in the late 1980s. Massive amounts of data and experience were accumulated throughout the years. Moreover, considerable research was conducted into matrix and fracture characterization and production mechanisms (Payne 1988; Beliveau 1989; Beliveau et al. 1993; Malik et al. 2006; McKishnie et al. 2005). Nevertheless, the success of enhanced recovery still depends on further research into the matrix heterogeneity, NFN geometry, and fracture/matrix interaction. Developments in computational and analytical methods have provided us with some useful tools, which facilitate the method described below. This paper describes how integrated fracture and matrix characterization using static and dynamic data helped us to construct and validate a discrete 3D fracture network embedded into reservoir matrix. Furthermore, we present the statistical analysis of designed flow simulations used to clarify the role of NFN properties in the reservoir performance.