Analysis and Interpretations of Pressure Data from the Hydraulic Fracturing Test Site (HFTS)
- Tianyu Li (Pioneer Natural Resources) | Weichun Chu (Pioneer Natural Resources) | Paul A. Leonard (Pioneer Natural Resources)
- Document ID
- Unconventional Resources Technology Conference
- SPE/AAPG/SEG Unconventional Resources Technology Conference, 22-24 July, Denver, Colorado, USA
- Publication Date
- Document Type
- Conference Paper
- 2019. Unconventional Resources Technology Conference
- 18 in the last 30 days
- 405 since 2007
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Three different types of analysis were performed on high-frequency bottomhole pressure data acquired in the Hydraulic Fracturing Test Site (HFTS; Ciezobka et al., 2018) program. The pressure data was made available by Laredo Petroleum Incorporated (LPI) and the Gas Technology Institute (GTI) through participation in the HFTS joint industry project. Rate transient analysis (RTA), pressure interference test (PIT) analysis, and reservoir pressure depletion analysis of production and pressure data were performed to better understand the performance of these hydraulically fractured Wolfcamp reservoirs of the southeastern Midland Basin. Unconventional RTA, PIT analysis, and reservoir depletion analysis of the HFTS pressure data provides three different perspectives to describe fracture systems in the formation. The study of these combined attributes of this unique dataset provides new insights about pressure communication and reservoir drainage of the Wolfcamp A and Wolfcamp B in the HFTS area.
Hydraulic fractures generated during multi-stage hydraulic fracturing operations often have complex geometries (Cipolla et.al, 2008). Estimating the dimensions of complex fracture networks is one of the biggest challenges of evaluating hydraulically fractured reservoirs. Utilizing high frequency bottomhole pressure (BHP) data, unconventional RTA provides a method to evaluate effective fracture dimensions with advantages of low marginal cost and simplicity. Chu et al. (2017) demonstrated the workflow to analyze multiphase rate transient data using examples of Permian Wolfcamp horizontal wells. In this study, a similar workflow is applied to BHP data collected from 11 Wolfcamp horizontal wells in the HFTS project.
High frequency BHP data collected during well interference tests can also be utilized to identify inter-well communication. Over the years, spacing between wells on a multi-well pad has been altered, along with fracture designs, to improve reservoir development efficiency. Larger fracturing treatments have been performed to increase well productivity. Interaction between nearby producing wells is more likely to happen with increasing fracture length and closer well spacings. Understanding the magnitude of fracture communication is therefore important for optimizing well spacing with fracturing treatment sizes. Communication between producing wells can be detected from pressure response at an observation well to significant rate changes at an active well, such as a shut-in (SI) or bring-online (BOL). The process is called a pressure interference test (PIT). PITs are widely used in conventional reservoirs to determine inter-well reservoir properties (Kamal, 1983). In unconventional shale reservoirs, analysis methods to understand the pressure interference test results have been developed in recent years. Sardinha et al. (2014) analyzed pressure interference between wells in Horn River Basin by calculating pressure hit percentage. Awada et al. (2015) identified the interference response time by looking at pressure derivatives. Roussel and Agrawal (2017) applied poroelastic geomechanical models to interpret pressure interference data and calculate fracture dimensions. In the HFTS project, two PITs were conducted among 11 horizontal wells at different times of production. Kumar et al. (2018) analyzed interference data from the first PIT by calculating field response times between source and observation wells. In this discussion, we follow the technique presented by Chu et al. (2018) for analyzing power-law PIT data to quantitatively diagnose well communication among HFTS wells. The magnitude of pressure interference (MPI) between communicating wells is calculated and compared for two PIT sequences conducted 18 months apart.
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