Reservoir and Fracture-Flow Characterization Using Novel Diagnostic Plots
- Xu Xue (Texas A&M University) | Changdong Yang (Texas A&M University) | Jaeyoung Park (Texas A&M University) | Vishal K. Sharma (Texas A&M University) | Akhil Datta-Gupta (Texas A&M University) | Michael J. King (Texas A&M University)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- June 2019
- Document Type
- Journal Paper
- 1,248 - 1,269
- 2019.Society of Petroleum Engineers
- Novel Diagnostic Plots, Reservoir and Fracture Flow Characterization
- 39 in the last 30 days
- 418 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
Multistage hydraulically fractured horizontal wells provide an effective means to exploit unconventional reservoirs. The current industry practice in the interpretation of field response often uses empirical decline-curve analysis or pressure-transient analysis/rate-transient analysis (PTA/RTA) for characterization of these reservoirs and fractures. These analytical tools depend on simplifying assumptions and do not provide a detailed description of the evolving reservoir-drainage volume accessed from a well. Understanding of the transient-drainage volume is essential for unconventional-reservoir and fracture assessment and optimization.
In our previous study (Yang et al. 2015), we developed a “data-driven” methodology for the production rate and pressure analysis of shale-gas and shale-oil reservoirs. There are no underlying assumptions of fracture geometry, reservoir homogeneity, and flow regimes in the method proposed in our previous study. This approach depends on the high-frequency asymptotic solution of the diffusivity equation in heterogeneous reservoirs. It allows us to determine the well-drainage volume and the instantaneous recovery ratio (IRR), which is the ratio of the produced volume to the drainage volume, directly from the production data. In addition, a new w(t) plot has been proposed to provide better insight into the depletion mechanisms and the fracture geometry. w(t) is the derivative of pore volume with respect to t.
In this paper, we build upon our previous approach to propose a novel diagnostic tool for the interpretation of the characteristics of (potentially) complex fracture systems and drainage volume. We have used the w(t) and IRR plots for the identification of characteristic signatures that imply complex fracture geometry, formation linear flow, partial reservoir completions, and fracture-interference/compaction effects during production. The w(t) analysis gives us the fracture surface area and formation diffusivity, while the IRR analysis provides additional information on fracture conductivity. In addition, quantitative analysis is conducted using the novel w(t) plot to interpret fracture-interference time, formation permeability, total fracture surface area, and stimulated reservoir volume (SRV).
The major advantages of this current approach are the model-free analysis without assuming planar fractures, homogeneous formation properties, and specific flow regimes. In addition, the w(t) plot captures high-resolution flow patterns not observed in traditional PTA/RTA analysis. The analysis leads to a simple and intuitive understanding of the transient-drainage volume and fracture conductivity. The results of the analysis are useful for hydraulic-fracturing-design optimization and matrix- and fracture-parameter estimation.
|File Size||2 MB||Number of Pages||22|
An, C., Alfi, M., Yan, B. et al. 2016. A New Study of Magnetic Nanoparticle Transport and Quantifying Magnetization Analysis in Fractured Shale Reservoir Using Numerical Modeling. J. Nat. Gas Sci. Eng. 28 (January): 502–521. https://doi.org/10.1016/j.jngse.2015.11.052.
Barker, J. A. 1988. A Generalized Radial Flow Model for Hydraulic Tests in Fractured Rock. Water Resour. Res. 24 (10): 1796–1804. https://doi.org/10.1029/WR024i010p01796.
Bourdet, D., Whittle, T., Douglas, A. et al. 1983. A New Set of Type Curves Simplifies Well Test Analysis. World Oil 196 (6): 95–106.
Cipolla, C. L., Lolon, E. P., Erdle, J. C. et al. 2010. Reservoir Modeling in Shale-Gas Reservoirs. SPE Res Eval & Eng 13 (4): 638–653. SPE-125530-PA. https://doi.org/10.2118/125530-PA.
Datta-Gupta, A., Xie, J., Gupta, N. et al. 2011. Radius of Investigation and Its Generalization to Unconventional Reservoirs. J Pet Technol 63 (7): 52–55. SPE-0711-0052-JPT. https://doi.org/10.2118/0711-0052-JPT.
Fetkovich, M. J. 1980. Decline Curve Analysis Using Type Curves. J Pet Technol 32 (6): 1065–1077. SPE-4629-PA. https://doi.org/10.2118/4629-PA.
Fujita, Y., Datta-Gupta, A., and King, M. J. 2015. A Comprehensive Reservoir Simulator for Unconventional Reservoirs Based on the Fast Marching Method and Diffusive Time of Flight. Presented at SPE Reservoir Simulation Symposium, Houston, 23–25 February. SPE-173269-MS. https://doi.org/10.2118/173269-MS.
Holditch, S. A. 2013. Unconventional Oil and Gas Resource Development—Let’s Do It Right. J. Unconven. Oil Gas Resour. 1–2 (June): 2–8. https://doi.org/10.1016/j.juogr.2013.05.001.
Ilk, D., Anderson, D. M., Stotts, G. W. J. et al. 2010. Production Data Analysis—Challenges, Pitfalls, Diagnostics. SPE Res Eval & Eng 13 (3): 538–552. SPE-102048-PA. https://doi.org/10.2118/102048-PA.
King, M. J., Wang, Z., and Datta-Gupta, A. 2016. Asymptotic Solutions of the Diffusivity Equation and Their Applications. Presented at SPE Europec featured at 78th EAGE Conference and Exhibition, Vienna, Austria, 30 May–2 June. SPE-180149-MS. https://doi.org/10.2118/180149-MS.
Kulkarni, K. N., Datta-Gupta, A., and Vasco, D. W. 2001. A Streamline Approach for Integrating Transient Pressure Data Into High-Resolution Reservoir Models. SPE J. 6 (3): 273–282. SPE-74135-PA. https://doi.org/10.2118/74135-PA.
Lee, W. J. and Sidle, R. E. 2010. Gas Reserves Estimation in Resource Plays. Presented at SPE Unconventional Gas Conference, Pittsburgh, Pennsylvania, 23–25 February. SPE-130102-MS. https://doi.org/10.2118/130102-MS.
Lee, W. J., Rollins, J. B., and Spivey, J. P. 2003. Pressure Transient Testing. Richardson, Texas: Textbook Series, Society of Petroleum Engineers.
Sethian, J. A. 1999. Fast Marching Methods. SIAM Rev. 41 (2): 199–235. https://doi.org/10.1137/S0036144598347059.
Song, B. and Ehlig-Economides, C. A. 2011. Rate-Normalized Pressure Analysis for Determination of Shale Gas Well Performance. Presented at the North American Unconventional Gas Conference and Exhibition, The Woodlands, Texas, 14–16 June SPE-144031-MS. https://doi.org/10.2118/144031-MS.
Tang, H., Chai, Z., Yan, B. et al. 2017. Application of Multi-Segment Well Modeling To Simulate Well Interference. Presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Austin, Texas, 24–26 July. URTEC-2668100-MS. https://doi.org/10.15530/URTEC-2017-2668100.
Valko, P. P. 2009. Assigning Value To Stimulation in the Barnett Shale: A Simultaneous Analysis of 7000 Plus Production Histories and Well Completion Records. Presented at SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, 19–21 January. SPE-119369-MS. https://doi.org/10.2118/119369-MS.
Vasco, D. W. and Datta-Gupta, A. 1999. Asymptotic Solutions for Solute Transport: A Formalism for Tracer Tomography. Water Resour. Res. 35 (1): 1–16. https://doi.org/10.1029/98WR02742.
Winestock, A. G. and Colpitts, G. P. 1965. Advances in Estimating Gas Well Deliverability. J Can Pet Technol 4 (3): 111–119. PETSOC-65-03-01. https://doi.org/10.2118/65-03-01.
Xie, J., Yang, C., Gupta, N. et al. 2014. Integration of Shale-Gas-Production Data and Microseismic for Fracture and Reservoir Properties With the Fast Marching Method. SPE J. 20 (2): 347–359. SPE-161357-PA. https://doi.org/10.2118/161357-PA.
Xie, J., Yang, C., Gupta, N. et al. 2015. Depth of Investigation and Depletion in Unconventional Reservoirs With Fast-Marching Methods. SPE J. 20 (4): 831–841. SPE-154532-PA. https://doi.org/10.2118/154532-PA.
Yang, C., Sharma, V. K., Datta-Gupta, A. et al. 2015. A Novel Approach for Production Transient Analysis of Shale Gas/Oil Reservoirs. Presented at the Unconventional Resources Technology Conference, San Antonio, Texas, 20–22 July. URTEC-2176280-MS. https://doi.org/10.15530/URTEC-2015-2176280.
Yang, C., Sharma, V. K., Datta-Gupta, A. et al. 2017a. Novel Approach for Production Transient Analysis of Shale Reservoirs Using the Drainage Volume Derivative. J. Pet. Sci. Eng. 159 (November): 8–24. https://doi.org/10.1016/j.petrol.2017.09.041.
Yang, C., Xue, X., King, M. J. et al. 2017b. Flow Simulation of Complex Fracture Systems With Unstructured Grids Using the Fast Marching Method. Presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Austin, Texas, 24–26 July. URTEC-2691393-MS. https://doi.org/10.15530/URTEC-2017-2691393.
Zhang, S. and Zhu, D. 2017. Inversion of Downhole Temperature Measurements in Multistage Fracture Stimulation in Horizontal Wells. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 9–11 October. SPE-187322-MS. https://doi.org/10.2118/187322-MS.
Zhang, Y., Bansal, N., Fujita, Y. et al. 2016. From Streamlines to Fast Marching: Rapid Simulation and Performance Assessment of Shale-Gas Reservoirs by Use of Diffusive Time of Flight as a Spatial Coordinate. SPE J. 21 (5): 1883–1898. SPE-168997-PA. https://doi.org/10.2118/168997-PA.
Zhang, Y., Yang, C., King, M. J. et al. 2013. Fast-Marching Methods for Complex Grids and Anisotropic Permeabilities: Application To Unconventional Reservoirs. Presented at the SPE Reservoir Simulation Symposium, The Woodlands, Texas, 18–20 February. SPE-163637-MS. https://doi.org/10.2118/163637-MS.
Zhou, J., Huang, H., Deo, M. et al. 2015. A New Physics-Based Modeling of Multiple Non-Planar Hydraulic Fractures Propagation. Presented at Unconventional Resources Technology Conference, San Antonio, Texas, 20–22 July. URTEC-2170875-MS. https://doi.org/10.15530/URTEC-2015-2170875.