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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 In this case study, we apply a novel fracture imaging and interpretation workflow to take a systematic look at hydraulic fractures captured during thorugh fracture coring at the Hydraulic Fracturing Test Site (HFTS) in Midland Basin. Digital fracture maps rendered using high resolution 3D laser scans are analyzed for fracture morphology and roughness. Analysis of hydraulic fracture faces show that the roughness varies systematically in clusters with average cluster separation of approximately 20' along the core. While isolated smooth hydraulic fractures are observed in the dataset, very rough fractures are found to be accompanied by proximal smoother fractures. Roughness distribution also helps understand the effect of stresses on fracture distribution. Locally, fracture roughness seems to vary with fracture orientations indicating possible inter-fracture stress effects. At the scale of stage lengths however, we see evidence of inter-stage stress effects. We also observe fracture morphology being strongly driven by rock properties and changes in lithology. Identified proppant distribution along the cored interval is also correlated with roughness variations and we observe strong positive correlation between proppant concentrations and fracture roughness at the local scale. Finally, based on the observed distribution of hydraulic fracture properties, we propose a conceptual spatio-temporal model of fracture propagation which can help explain the hydraulic fracture roughness distribution and ties in other observations as well.
Suarez-Rivera, Roberto (W. D. Von Gonten Laboratories) | Panse, Rohit (W. D. Von Gonten Laboratories) | Sovizi, Javad (Baker Hughes) | Dontsov, Egor (ResFrac Corporation) | LaReau, Heather (BP America Production Company, BPx Energy Inc.) | Suter, Kirke (BP America Production Company, BPx Energy Inc.) | Blose, Matthew (BP America Production Company, BPx Energy Inc.) | Hailu, Thomas (BP America Production Company, BPx Energy Inc.) | Koontz, Kyle (BP America Production Company, BPx Energy Inc.)
Abstract Predicting fracture behavior is important for well placement design and for optimizing multi-well development production. This requires the use of fracturing models that are calibrated to represent field measurements. However, because hydraulic fracture models include complex physics and uncertainties and have many variables defining these, the problem of calibrating modeling results with field responses is ill-posed. There are more model variables than can be changed than field observations to constrain these. It is always possible to find a calibrated model that reproduces the field data. However, the model is not unique and multiple matching solutions exist. The objective and scope of this work is to define a workflow for constraining these solutions and obtaining a more representative model for forecasting and optimization. We used field data from a multi-pad project in the Delaware play, with actual pump schedules, frac sequence, and time delays as used in the field, for all stages and all wells. We constructed a hydraulic fracturing model using high-confidence rock properties data and calibrated the model to field stimulation treatment data varying the two model variables with highest uncertainty: tectonic strain and average leak-off coefficient, while keeping all other model variables fixed. By reducing the number of adjusting model variables for calibration, we significantly lower the potential for over-fitting. Using an ultra-fast hydraulic fracturing simulator, we solved a global optimization problem to minimize the mismatch between the ISIPs and treatment pressures measured in the field and simulated by the model, for all the stages and all wells. This workflow helps us match the dominant ISIP trends in the field data and delivers higher confidence predictions in the regional stress. However, the uncertainty in the fracture geometry is still large. We also compared these results with traditional workflows that rely on selecting representative stages for calibration to field data. Results show that our workflow defines a better global optimum that best represents the behavior of all stages on all wells, and allows us to provide higher-confidence predictions of fracturing results for subsequent pads. We then used this higher confidence model to conduct sensitivity analysis for improving the well placement in subsequent pads and compared the results of the model predictions with the actual pad results.
ABSTRACT The industry is facing significant challenges due to the recent downturn in oil prices, particularly for the development of tight reservoirs. It is more critical than ever to 1) identify the sweet spots with less uncertainty and 2) optimize the completion-design parameters. The overall objective of this study is to quantify and compare the effects of reservoir quality and completion intensity on well productivity. We developed a supervised fuzzy clustering (SFC) algorithm to rank reservoir quality and completion intensity, and analyze their relative impacts on wells' productivity. We collected reservoir properties and completion-design parameters of 1,784 horizontal oil and gas wells completed in the Western Canadian Sedimentary Basin. Then, we used SFC to classify 1) reservoir quality represented by porosity, hydrocarbon saturation, net pay thickness and initial reservoir pressure; and 2) completion-design intensity represented by proppant concentration, number of stages and injected water volume per stage. Finally, we investigated the relative impacts of reservoir quality and completion intensity on wells' productivity in terms of first year cumulative barrel of oil equivalent (BOE). The results show that in low-quality reservoirs, wells' productivity follows reservoir quality. However, in high-quality reservoirs, the role of completion-design becomes significant, and the productivity can be deterred by inefficient completion design. The results suggest that in low-quality reservoirs, the productivity can be enhanced with less intense completion design, while in high-quality reservoirs, a more intense completion significantly enhances the productivity. Keywords Reservoir quality; completion intensity; supervised fuzzy clustering, approximate reasoning,tight reservoirs development
Brinkley, Kourtney (Devon Energy) | Ingle, Trevor (Devon Energy) | Haffener, Jackson (Devon Energy) | Chapman, Philip (Devon Energy) | Baker, Scott (Devon Energy) | Hart, Eric (Devon Energy) | Haustveit, Kyle (Devon Energy) | Roberts, Jon (Devon Energy)
Abstract This case study details the use of Sealed Wellbore Pressure Monitoring (SWPM) to improve the characterization of fracture geometry and propagation during stimulation of inter-connected stacked pay in the South Texas Eagle Ford Shale. The SWPM workflow utilizes surface pressure gauges to detect hydraulically induced fracture arrivals athorizontal monitor locations adjacent to the stimulated wellbore (Haustveit et al. 2020). A stacked and staggered development in Dewitt County provided the opportunity to jointly evaluateprimary completion and recompletion efforts spanning three reservoir target intervals. Fivemonitor wells at varying distances across the unit were employed for SWPM during the stimulation of four wells. An operational overview, analysis of techniques, correlation with seismic attributes, image log interpretations, and fracture model calibration are provided. Outputs from this workflow allow for a refined analysis ofthe overall completion strategy. The high-density, five well monitor array recorded a total of 160 fracture arrivals at varying vertical and lateral distances, with far-field fracture arrivalsprovidingsignificant insight into propagation rates and geometry. Apronounced trend occurred in both arrival frequency and volumes pumped as monitor locations increased in distance from the treatment well. Specific to target zone isolation, it was identified that traversing vertically in section through a high stress interval yielded a 30% reduction inarrival frequency. An indirect relationship between horizontal distance and arrival frequency was also observed when monitoring from the same interval. A decrease in fracture arrivals from 70% down to 8% was realized as offset distance increased from 120 to 1,700 ft. The results from this study have proven to be instrumental in guiding interdisciplinary discussion. Assessing fracture geometry and propagation during stimulation, particularly in the co-development of a stacked pay reservoir, is paramount to the determination of proper completion volume, perforation design, and well spacing. Leveraging the observations of SWPM ultimately provides greater confidence in field development strategy and economic optimization.
Abstract Maximum horizontal stress (SH) and stress path (change of SH and minimum horizontal stress with depletion) are the two most difficult parameters to define for an oilfield geomechanical model. Understanding these in-situ stresses is critical to the success of operations and development, especially when production is underway, and the reservoir depletion begins. This paper introduces a method to define them through the analysis of actual minifrac data. Field examples of applications on minifrac failure analysis and operational pressure prediction are also presented. It is commonly accepted that one of the best methods to determine the minimum horizontal stress (Sh) is the use of pressure fall-off analysis of a minifrac test. Unlike Sh, the magnitude of SH cannot be measured directly. Instead it is back calculated by using fracture initiation pressure (FIP) and Sh derived from minifrac data. After non-depleted Sh and SH are defined, their apparent Poisson's Ratios (APR) are calculated using the Eaton equation. These APRs define Sh and SH in virgin sand to encapsulate all other factors that influence in-situ stresses such as tectonic, thermal, osmotic and poro-elastic effects. These values can then be used to estimate stress path through interpretation of additional minifrac data derived from a depleted sand. A geomechanical model is developed based on APRs and stress paths to predict minifrac operation pressures. Three cases are included to show that the margin of error for FIP and fracture closure pressure (FCP) is less than 2%, fracture breakdown pressure (FBP) less than 4%. Two field cases in deep-water wells in the Gulf of Mexico show that the reduction of SH with depletion is lower than that for Sh.
Abstract With a recent trend in increased infill well development in the Midland basin and other unconventional plays, it has been shown that depletion has a significant impact on hydraulic fracture propagation. This is largely because production drawdown causes in-situ stress changes, resulting in asymmetric fracture growth toward the depleted regions. In turn, this can have a negative impact on production capacity. For the initial part of this study, an infill child well was drilled and completed adjacent to a parent well that had been producing for two years. Due to drilling difficulties, the child well was steered to a new target zone located 125 feet above the original target. However, relative to the original target, treatment data from the new zone indicated abnormal treatment responses leading to a study to evaluate the source of these variations and subsequent mitigation. The initial study was conducted using a pore pressure estimation derived from drill bit geomechanics data to investigate depletion effects on the infill child well. The pore pressure results were compared to the child well treatment responses and bottom hole pressure measurements in the parent well. Following the initial study, additional hydraulic fracture modeling studies were conducted on a separate pad to investigate depletion around the infill wells, determine optimal well spacing for future wells given the level of depletion, and optimize treatment designs for future wells in similar depletion scenarios. A depletion model workflow was implemented based on integrating hydraulic fracture modeling and reservoir analytics for future infill pad development. The geomechanical properties were calibrated by DFIT results and pressure matching of the parent well treatments for the in-situ virgin conditions. Parent well fracture geometries were used in an RTA for an analytical approach of estimating drainage area of the parent wells. These were then applied to a depletion profile in the hydraulic fracture model for well spacing analysis and treatment design sensitivities. Results of the initial study indicated that stages in the new, higher interval had higher breakdown pressures than the lower interval. Additionally, the child well drilled in the lower interval had normal breakdown pressures in line with the parent well treatments. This suggests that treatment differences in the wells were ultimately due to depletion of the offset parent well. Based on the modeling efforts, optimal infill well spacing was determined based on the on-production time of the parent wells. The optimal treatment designs were also determined under the same conditions to minimize offset frac hits and unnecessary completion costs. This case study presents the use of a multi-disciplinary approach for well spacing and treatment optimization. The integration of a novel method of estimating pore pressure and depletion modeling workflows were used in an inventive way to understand depletion effects on future development.
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 The purpose of this paper is to present a technique to estimate hydraulic fracture (HF) length, fracture conductivity, and fracture efficiency using simple and rapid but rigorous reservoir simulation matching of historical production, and where available, pressure. The methodology is particularly appropriate for analysis of horizontal wells with multiple fractures in tight unconventional or unconventional resource plays. In our discussion, we also analyze the differences between the results from decline curve analysis (DCA) approach and the Science Based Forecasting (SBF) results that this work proposes. When we characterize fracture properties with SBF, we can do a better job of forecasting than if we randomly combine fracture properties and reservoir permeability together in a decline-curve trend. The forecasts are significantly different with SBF, therefore fracture characterization plays an important role and SBF uses this characterization to produce different (and better) forecasts.
Abstract Assessment of in-situ stresses and hydraulic fracturing stimulation are two critical parameters for successful heat extraction from Enhanced Geothermal Systems (EGS). Fracture injection and injection/flow back tests are two conventional techniques for estimating the minimum horizontal stress in subsurface formations. Because of the heat exchange during the test, ultra-low permeability of the host rock, and natural fractures, the conventional methods yield inaccurate results in geothermal reservoirs. In this paper, we present a new methodology based on the signal processing approach for analyzing DFIT in geothermal reservoirs. The applicability of our technique is demonstrated using several test data from the Utah FORGE project. The main advantage of our methodology is that it does not depend on any assumption regarding fracture geometry and rock properties. Also, unlike most similar studies, we consider the effect of heat exchange between fracturing fluid and the hot rock. In our methodology, the recorded pressure and temperature are treated as signals, and a wavelet transform is applied to separate them to high pass (noise) and low pass (approximation) components. Using the noise energy of the two signals, we then identify different events such as fracture closure. Also, an analytical technique is used to correct the pressure by extracting the effect of fluid compressibility and heat exchange between the rock and injected fluid. We show that the G-Function technique underestimates the minimum horizontal stress in tight formations. After applying the corrections for pressure, the underestimation becomes more apparent. However, our approach gives consistent results before and after the pressure correction. Using the developed technique, we analyzed several injection tests from the Utah FORGE project. Both recorded pressure and temperature have been analyzed. Results show that the energy of the pressure signal noise decreases to a minimum level at the fracture closure. The fracture closure is confirmed by applying the same technique on the recorded temperature. The moment of closure using the proposed methodology is compared to the G-function approach, before and after correction of the pressure for temperature. Unlike physics-based techniques, the proposed method does not have any pre-assumption about the fracture's geometry or type of the well. The method solely relies on the pressure and temperature signals that are recorded during the injection and shut-in periods. Combining several analysis techniques to analyze DFIT (including the analysis of monitored temperature for a geothermal reservoir) is unique and maybe the first of its kind.