Co-Development of Multiple Targets in Permian Unconventional Reservoirs

Authors
Richard Cao (Shell Exploration and Production Co.) | Chaohui Chen (Shell Exploration and Production Co.) | Alejandro Girardi (Shell Exploration and Production Co.) | Ruijian Li (Shell Exploration and Production Co.) | Nitin Chowdhury (Shell Exploration and Production Co.)
DOI
https://doi.org/10.2118/195910-MS
Document ID
SPE-195910-MS
Publisher
Society of Petroleum Engineers
Source
SPE Annual Technical Conference and Exhibition, 30 September - 2 October, Calgary, Alberta, Canada
Publication Date
2019
Document Type
Conference Paper
Language
English
ISBN
978-1-61399-663-8
Copyright
2019. Society of Petroleum Engineers
Keywords
Stochastic Modeling, Well Interference, Well Spacing, Unconventional Reservoirs, Co-development
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Abstract

Optimum co-development layout of multiple targets for unconventional reservoirs is extremely challenging due to complex 3-dimentional well interactions, stochastic well performance, complex fracture geometry, dynamic SRV/DRV evolution, heterogeneous rock properties, various operating conditions, and different economic drivers. In this study, an integrated workflow is developed and applied for co-development of multiple targets in Permian unconventional reservoirs.

In this workflow, the field pilot and trial measurements, Microseismic, geochemistry measurement, data analytics, detailed geomechanical and reservoir modeling, stochastic multiple history matching and forecast, all combined to quantify the horizontal and vertical interference factors and obtain production profiles for different co-development designs. The stochastic behavior of the well performance is explored from three different aspects: static rock properties, dynamic fracturing, and production. The SRV/DRV evolution are presented as the probability distribution function of half fracture length from Microseismic data and effective drainage half-length from stochastic modeling.

File Size  1 MBNumber of Pages   15

Cao, R., Ma, L., & Blount, A. (2016, September 21). Maximizing the Value of Unconventional Liquid Rich Shale Development with Integrated Cross-Discipline Approach. Society of Petroleum Engineers. doi:10.2118/181768-MS

Cao, R., Li, R., Girardi, A., Chowdhury, N., & Chen, C. (2017, July 24). Well Interference and Optimum Well Spacing for Wolfcamp Development at Permian Basin. Unconventional Resources Technology Conference. doi:10.15530/URTEC-2017-2691962

Bhattacharya, S., Lake, E., Liu, X., Dombrowski, R., Cao, R., & Girardi, A. (2018, August 9). Increase Net Present Value and Reduce Completion Cost by Using an In-House Automated Fracture Design, Reservoir Simulator and Optimization Workflow for Well Spacing and Completions Design. Unconventional Resources Technology Conference. doi:10.15530/URTEC-2018-2902106

Cao, R., Chen, C., Li, R., Firincioglu, T., Ozgen, C., Croft, T., Chowdhury, N. (2018, August 9). Integrated Stochastic Workflow for Optimum Well Spacing with Data Analytics, Pilots, Geomechanical-Reservoir Modeling, and Economic Analysis. Unconventional Resources Technology Conference. doi:10.15530/URTEC-2018-2902138

Mhiri, A., Blasingame, T. A., & Moridis, G. J. (2015, September 28). Stochastic Modeling of a Fracture Network in a Hydraulically Fractured Shale-Gas Reservoir. Society of Petroleum Engineers. doi:10.2118/175021-MS

Blount, A., Croft, T., Driskill, B., McMullen, A., & Durand, M. (2018, August 9). Developing Predictive Power in the Permian: Leveraging Advanced Petrophysics to Deliver Cash to the Business. Unconventional Resources Technology Conference. doi:10.15530/URTEC-2018-2903087

Zhan, L., Fair, P. S., Dombrowski, R. J., Quint, E. N., & Cao, R. (2017, October 9). Estimating Ultra Low Permeability at Multiple Locations Using Simultaneous Impulse Tests: A Fit for Purpose Pressure Transient Solution and Its Field Application. Society of Petroleum Engineers. doi:10.2118/187063-MS

Cao, R., Liu, C., & Brennan, C. (2018, August 9).Understand the Early Indicators for Long-Term Performance of Unconventional Wells. Unconventional Resources Technology Conference. doi:10.15530/URTEC-2018-2903016

Guo, Z., Chen, C., Gao, G., Cao, R., Li, R., & Liu, C. (2017, July 24).EUR Assessment of Unconventional Assets Using Machine Learning and Distributed Computing Techniques. Unconventional Resources Technology Conference. doi:10.15530/URTEC-2017-2659996

Zhan, L., Fair, P. S., Dombrowski, R. J., Quint, E. N., & Cao, R. (2018, August 1). Estimating Ultralow Permeability at Multiple Locations Using Simultaneous-Impulse Tests: A Fit-for-Purpose Pressure-Transient Solution and Its Field Application. Society of Petroleum Engineers. doi:10.2118/187063-PA

Chen, C., Gao, G., Li, R., Cao, R., Chen, T., Vink, J. C., & Gelderblom, P. (2017, February 20). Integration of Distributed Gauss-Newton with Randomized Maximum Likelihood Method for Uncertainty Quantification of Reservoir Performance. Society of Petroleum Engineers. doi:10.2118/182639-MS

Xiong, H., Liu, S., Feng, F., Liu, S., & Yue, K. (2019, January 29). Optimize Completion Design and Well Spacing with the Latest Complex Fracture Modeling & Reservoir Simulation Technologies: A Permian Basin Case Study with Seven Wells. Society of Petroleum Engineers. doi:10.2118/194367-MS

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