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Nicholson, A. Kirby (Pressure Diagnostics Ltd.) | Bachman, Robert C. (Pressure Diagnostics Ltd.) | Scherz, R. Yvonne (Endeavor Energy Resources) | Hawkes, Robert V. (Cordax Evaluation Technologies Inc.)
Abstract Pressure and stage volume are the least expensive and most readily available data for diagnostic analysis of hydraulic fracturing operations. Case history data from the Midland Basin is used to demonstrate how high-quality, time-synchronized pressure measurements at a treatment and an offsetting shut-in producing well can provide the necessary input to calculate fracture geometries at both wells and estimate perforation cluster efficiency at the treatment well. No special wellbore monitoring equipment is required. In summary, the methods outlined in this paper quantifies fracture geometries as compared to the more general observations of Daneshy (2020) and Haustveit et al. (2020). Pressures collected in Diagnostic Fracture Injection Tests (DFITs), select toe-stage full-scale fracture treatments, and offset observation wells are used to demonstrate a simple workflow. The pressure data combined with Volume to First Response (Vfr) at the observation well is used to create a geometry model of fracture length, width, and height estimates at the treatment well as illustrated in Figure 1. The producing fracture length of the observation well is also determined. Pressure Transient Analysis (PTA) techniques, a Perkins-Kern-Nordgren (PKN) fracture propagation model and offset well Fracture Driven Interaction (FDI) pressures are used to quantify hydraulic fracture dimensions. The PTA-derived Farfield Fracture Extension Pressure, FFEP, concept was introduced in Nicholson et al. (2019) and is summarized in Appendix B of this paper. FFEP replaces Instantaneous Shut-In Pressure, ISIP, for use in net pressure calculations. FFEP is determined and utilized in both DFITs and full-scale fracture inter-stage fall-off data. The use of the Primary Pressure Derivative (PPD) to accurately identify FFEP simplifies and speeds up the analysis, allowing for real time treatment decisions. This new technique is called Rapid-PTA. Additionally, the plotted shape and gradient of the observation-well pressure response can identify whether FDI's are hydraulic or poroelastic before a fracture stage is completed and may be used to change stage volume on the fly. Figure 1: Fracture Geometry Model with FDI Pressure Matching Case studies are presented showing the full workflow required to generate the fracture geometry model. The component inputs for the model are presented including a toe-stage DFIT, inter-stage pressure fall-off, and the FDI pressure build-up. We discuss how to optimize these hydraulic fractures in hindsight (look-back) and what might have been done in real time during the completion operations given this workflow and field-ready advanced data-handling capability. Hydraulic fracturing operations can be optimized in real time using new Rapid-PTA techniques for high quality pressure data collected on treating and observation wells. This process opens the door for more advanced geometry modeling and for rapid design changes to save costs and improve well productivity and ultimate recovery.
Abstract Market-induced production shut-downs and restarts offer us an opportunity to gather step-rate and shut-in data for pressure transient analysis (PTA) and rate transient analysis (RTA). In this study, we present a unified transient analysis (UTA) to combine PTA and RTA in a single framework. In this new approach continuous production data, step-rate data, shut-in data and re-start data can be visualized and analyzed in a single superposition plot, which can be used to estimate both and infer formation pore pressure in a holistic manner by utilizing all available data. Most importantly, we show that traditional log-log and square root of time plots can lead to false interpretation of the termination of linear-flow or power-law behavior. Field cases are presented to demonstrate the superiority of the newly introduced superposition plot, along with discussion on the calibration of long-term bottom-hole pressure with short-term measurements.
Abstract A breakthrough patent-pending pressure diagnostic technique using offset sealed wellbores as monitoring sources was introduced at the 2020 Hydraulic Fracturing Technology Conference. This technique quantifies various hydraulic fracture parameters using only a surface gauge mounted on the sealed wellbore(s). The initial concept, operational processes, and analysis techniques were developed and deployed by Devon Energy. By scaling and automating the process, Sealed Wellbore Pressure Monitoring (SWPM) is now available to the industry as a repeatable workflow that greatly reduces analysis time and improves visualizations to aid data interpretations. The authors successfully automated the SWPM analysis procedure using a cloud-based software platform designed to ingest, process, and analyze high-frequency hydraulic fracturing data. The minimum data for the analysis consists of the standard frac treatment data combined with the high-resolution pressure gauge data for each sealed wellbore. The team developed machine learning algorithms to identify the key events required by a sealed wellbore pressure analysis: the start, end, and magnitude of each pressure response detected in the sealed wellbore(s) while actively fracturing offset wells. The result is a rapid, repeatable SWPM analysis that minimizes individual interpretation biases. The primary deliverables from SWPM analyses are the Volumes to First Response (VFR) on a per stage basis. In many projects, multiple pressure responses within a single stage have been observed, which provides valuable insight into fracture network complexity and cluster/stage efficiency. Various methods are used to visualize and statistically analyze the data. A scalable process facilitates creating a statistical database for comparing completion designs that can be segmented by play, formation, or other geological variations. Completion designs can then be optimized based upon the observed well responses. With enough observations and based on certain spacings, probabilities of when to expect fracture interactions could be assigned for different plays.
Zeinabady, Danial (University of Calgary) | Zanganeh, Behnam (University of Calgary, Chevron Canada Resources) | Shahamat, Sadeq (Birchcliff Energy Ltd.) | Clarkson, Christopher R. (University of Calgary)
Abstract The DFIT flowback analysis (DFIT-FBA) method, recently developed by the authors, is a new approach for obtaining minimum in-situ stress, reservoir pressure, and well productivity index estimates in a fraction of the time required by conventional DFITs. The goal of this study is to demonstrate the application of DFIT-FBA to hydraulic fracturing design and reservoir characterization by performing tests at multiple points along a horizontal well completed in an unconventional reservoir. Furthermore, new corrections are introduced to the DFIT-FBA method to account for perforation friction, tortuosity, and wellbore unloading during the flowback stage of the test. The time and cost efficiency associated with the DFIT-FBA method provides an opportunity to conduct multiple field tests without delaying the completion program. Several trials of the new method were performed for this study. These trials demonstrate application of the DFIT-FBA for testing multiple points along the lateral of a horizontal well (toe stage and additional clusters). The operational procedure for each DFIT-FBA test consists of two steps: 1) injection to initiate and propagate a mini hydraulic fracture and 2) flowback of the injected fluid on surface using a variable choke setting on the wellhead. Rate transient analysis methods are then applied to the flowback data to identify flow regimes and estimate closure and reservoir pressure. Flowing material balance analysis is used to estimate the well productivity index for studied reservoir intervals. Minimum in-situ stress, pore pressure and well productivity index estimates were successfully obtained for all the field trials and validated by comparison against a conventional DFIT. The new corrections for friction and wellbore unloading improved the accuracy of the closure and reservoir pressures by 4%. Furthermore, the results of flowing material balance analysis show that wellbore unloading might cause significant over-estimation of the well productivity index. Considerable variation in well productivity index was observed from the toe stage to the heel stage (along the lateral) for the studied well. This variation has significant implications for hydraulic fracture design optimization, particularly treatment pressures and volumes.
Abstract Recovery factor for multi-fractured horizontal wells (MFHWs) at development spacing in tight reservoirs is closely related to the effective horizontal and vertical extents of the hydraulic fractures. Direct measurement of pressure depletion away from the existing producers can be used to estimate the extent of the hydraulic fractures. Monitoring wells equipped with downhole gauges, DFITs from multiple new wells close to an existing (parent) well, and calculation of formation pressure from drilling data are among the methods used for pressure depletion mapping. This study focuses on acquisition of pressure depletion data using multi-well diagnostic fracture injection tests (DFITs), analysis of the results using reservoir simulation, and integration of the results with production data analysis of the parent well using rate-transient analysis (RTA) and reservoir simulation. In this method, DFITs are run on all the new wells close to an existing (parent) well and the data is analyzed to estimate reservoir pressure at each DFIT location. A combination of the DFIT results provides a map of pressure depletion around the existing well, while production data analysis of the parent well provides fracture conductivity and surface area and formation permeability. Furthermore, reservoir simulation is tuned such that it can also match the pressure depletion map by adjusting the system permeability and fracture geometry of the parent well. The workflow of this study was applied to two field case from Montney formation in Western Canadian Sedimentary Basin. In Field Case 1, DFIT results from nine new wells were used to map the pressure depletion away from the toe fracture of a parent well (four wells toeing toward the parent well and five wells in the same direction as the parent). RTA and reservoir simulation are used to analyze the production data of the parent well qualitatively and quantitatively. The reservoir model is then used to match the pressure depletion map and the production data of the parent well and the outputs of the model includes hydraulic fracture half-lengths on both sides of the parent well, formation permeability, fracture surface area and fracture conductivity. In Field Case 2, the production data from an existing well and DFIT result from a new well toeing toward the existing wells were incorporated into a reservoir simulation model. The model outputs include system permeability and fracture surface area. It is recommended to try the method for more cases in a specific reservoir area to get a statistical understanding of the system permeability and fracture geometry for different completion designs. This study provides a practical and cost-effective approach for pressure depletion mapping using multi-well DFITs and the analysis of the resulting data using reservoir simulation and RTA. The study also encourages the practitioners to take every opportunity to run DFITs and gather pressure data from as many well as possible with focus on child wells.
Summary The pressure decline data after the end of a hydraulic fracture stage are sometimes monitored for an extended period of time. However, to the best of our knowledge, these data are not analyzed and are often ignored or underappreciated because of a lack of suitable models for the closure of propped fractures. In this study, we present a new approach to model and analyze pressure decline data that are available in unconventional horizontal wells with multistage, transverse hydraulic fracturing. The methods presented in this study allow us to quantify closure stress and average pore pressure inside the stimulated reservoir volume (SRV) and to infer the uniformity of proppant distribution without additional data acquisition costs. For the first time, field data of diagnostic fracture injection test (DFIT), flowback, and pressure decline of main fracturing stages from the same well are compared and analyzed. We found that the early-time main fracturing stage pressure decline trend is controlled by fracture tip extension, followed by progressive hydraulic fracture closure on the proppant pack, whereas late-time pressure decline reflects linear flow. When DFIT data are not available, pressure decline analysis of a main hydraulic fracturing stage can be a substitution if it can be monitored for an extended period to allow fracture closure on proppants and asperities.
Abstract Pressure-transient analysis (PTA) is widely used in the industry to estimate fracture half-length, height, and skin due to hydraulic fracturing as well as reservoir parameters. PTA studies focus on pressure data from long shut-in periods and diagnostic fracture injection tests (DFITs), while analyzing the pressure data recorded during the hydraulic fracture treatment has been overlooked. This paper details the state-of-the-art in applying pressure transient analysis to better estimate hydraulic fracture conductivity and dimensions and improve treatment designs stage by stage. The initial portion of this paper describes the application of a novel and low-cost diagnostic method for post-fracture analysis. The bulk of the paper is dedicated to present case histories that illustrate the PTA of the recorded pressure data during treatment to obtain estimates of fracture dimensions and conductivity. The pressure recorded during each stage is processed to ensure the proper data quality and the pressure falloff at the end of the stage is filtered out. The pressure is then analyzed for multi-cluster, finite-conductivity fractures, to obtain the fracture half-length, conductivity, and leakoff. Calculated parameters from each stage are compared to provide insights into the hydraulic fracture design and confirm the adequacy of the treatment design along the well. The results from stage leakoff pressure analysis are very valuable in confirming relative fracture conductivity and providing a qualitative measure of fracture length and height. The total stimulated reservoir area (SRA) calculated using the proposed method yields comparable values to SRA obtained from buildup analysis. The information provided is as valuable and comparable as that from direct near-wellbore diagnostics, such as radioactive traces, temperature logging, real-time micro-seismic monitoring, and production logging. The paper proposes a novel, low-cost analytical PTA method for estimating fracture dimensions, skin, and leakoff coefficient. We illustrate – with several field cases – that conventional post-fracture techniques can be integrated with the stage by stage PTA analysis to provide not only a more consistent and systematic analysis but also a more accurate assessment of treatment effectiveness. The findings of this paper help improve the efficiency of multistage hydraulic fracturing stimulation of horizontal wells.
Abstract Castillo1 suggested the use of the G-Function plot based on the work of Nolte2. It has been a standard practice in the fracturing community to estimate the fracture closing pressure from a tangent to the G*dp/dg plot. In this analysis technique, the assumption is that a fracture has already developed under the high-pressure fracturing fluid. Then when the pumping is relaxed, one can estimate the fracture closing pressure. In many California waterfloods, the issue of maximum allowable injection gradient has been debated. Various solutions have been proposed to calculate a safe injection gradient. One method that has been promoted is the application of the G-function plot. In this paper, we maintain that this application can be misleading using the prescribed cartesian G function plots. We present the results of an extensive research study for analyzing pressure fall-off data using the G-Plot function. We studied a reappraisal of the G function plot using waterflood conditions where no prior fractures had formed, and no fracture closing pressure was meaningful or applicable. We show from analysis of generated data, using both numerical reservoir modeling and analytical derivations for a radial flow system, that fall-off tests analyzed using the cartesian G function can generate false indications of fracture closing where in fact, the entire injection has been based on radial flow homogeneous injection systems. We also studied systems with a pre-existing fracture before injection. We show that if such a reservoir system is subjected to injection and fall-off tests, again, one may compute a false indication of the irrelevant fracture closure pressure. We discuss how the cartesian scale used for the G function plot can be misleading for the analysis of fall-off test data.