Estimating Effective Fracture Pore Volume From Flowback Data and Evaluating Its Relationship to Design Parameters of Multistage-Fracture Completion
- Yingkun Fu (University of Alberta) | Hassan Dehghanpour (University of Alberta) | Dannel Obinna Ezulike (University of Alberta) | R. Steven Jones Jr. (Newfield Exploration Company)
- Document ID
- Society of Petroleum Engineers
- SPE Production & Operations
- Publication Date
- March 2017
- Document Type
- Journal Paper
- 2017.Society of Petroleum Engineers
- Fracture Characterization, Hydraulic Fracturing Design, Flowback Analysis
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- 631 since 2007
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Flowback data from seven multifractured horizontal tight oil/gas wells in Anadarko Basin show two separate regions during the single-phase water production. Region 1 shows a dropping casing pressure, and Region 2 shows a flattening casing pressure. This paper investigates the flowback behavior of the two regions, and illustrates how flowback data can be interpreted to estimate effective fracture pore volume, and to investigate its relationship to completion-design parameters. We construct diagnostic plots to understand the physics of Regions 1 and 2. Region 1 represents pressure depletion in fractures, and Region 2 represents the hydrocarbon breakthrough into the effective fracture network. The results of our analyses indicate that the duration of Region 1 depends on initial reservoir pressure and hydrocarbon type. We apply a previous flowback model (Abbasi et al. 2012, 2014) on Region 1 to estimate effective fracture pore volume, and also propose a procedure to estimate fracture compressibility by use of diagnostic-fracturing-injection-test (DFIT) data. The results suggest that the estimated effective fracture pore volume is very sensitive to fracture compressibility, and is generally larger than the final load-recovery volume, and less than the total injected-water volume. The results also suggest that most of the effective fractures are unpropped, and host the nonrecovered fracturing water. We investigate the relationship between the estimated effective fracture pore volumes and completion-design parameters, including total injected-water volume, proppant mass, gross perforated interval, and number of clusters, by use of the Pearson correlation-coefficient method. The results show that total injected-water volume, gross perforated interval, and the number of clusters are among the key design parameters for an optimal fracturing treatment. Higher total injected-water volume and closer cluster spacing generally lead to a larger effective fracture pore volume.
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