Cluster Spacing Optimization through Data Integration Workflow for Unconventional Jurassic Mudrocks, Saudi Arabia
- Ali Al-Momin (Saudi Aramco) | Karim Mechkak (Saudi Aramco) | Kirk Bartko (Saudi Aramco) | Kenneth McClelland (Saudi Aramco) | Roberto Tineo (Schlumberger) | Matthew Drouillard (Schlumberger) | Muhammad Nadeem (Schlumberger)
- Document ID
- Society of Petroleum Engineers
- SPE Hydraulic Fracturing Technology Conference and Exhibition, 24–26 January, The Woodlands, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2017. Society of Petroleum Engineers
- 3.2.7 Lifecycle Management and Planning, 7.6 Information Management and Systems, 7 Management and Information, 2 Well completion, 3.3 Well & Reservoir Surveillance and Monitoring, 3.3.1 Production Logging, 5.1.5 Geologic Modeling, 0.2.2 Geomechanics, 3.2 Well Operations and Optimization, 1.6.6 Directional Drilling, 3 Production and Well Operations, 1.6 Drilling Operations, 3 Production and Well Operations, 0.2 Wellbore Design
- Cluster Spacing, Fracture performance modeling, Fracture optimization, Unconventional gas
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One of main challenges operators face in evaluating the potential of unconventional reservoirs is the complex geologic nature of organic rich, fractured, laminated, and heterogeneous formations having implications on stimulation and production optimization. An area with a limited number of stimulated appraisal wells in the Jurassic mud rocks in Saudi Arabia was targeted for this study. The objective is to build and calibrate a multidisciplinary integrated workflow consisting of geologic, hydraulic fracture, and reservoir modeling to optimize the number of clusters and other completion parameters for a multi-well pad drilled in the subject area.
The workflow developed comprises integration of data analysis to evaluate reservoir and completion qualities and assess their impacts on production performance specifically for unconventional reservoirs. Petrophysical and geomechanical models were calibrated with core measurements. Logs from the horizontal lateral was integrated in the geomechanical model to analyze the hydraulic fracture stimulation by performing fracture pressure matching for all stages. The hydraulic fracture attributes from the fracture simulator were exported to the reservoir simulator. The surface production measurement together with the production log were used to calibrate the reservoir model.
The final calibrated workflow, including hydraulic fracture and reservoir models, was used to perform sensitivity analyses to optimize the cluster spacing and other completion parameters considering the geomechanical and reservoir constraints. Preliminary results suggest stress shadowing is not a major concern even with a short cluster spacing given the level of stress anisotropy in this formation. An optimum cluster spacing was determined based on long-term production performance. The results of this study were implemented in a pilot well pad to determine which completion variables were critical for optimizing well productivity and further calibration of the workflow.
The methodology adopted in this study identifies the major controlling factors of completion and reservoir parameters affecting well productivity for specific unconventional reservoirs. This workflow will help shorten the learning curve and increase the efficiency to reach the optimum stimulation design for the development phase.
|File Size||2 MB||Number of Pages||18|
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