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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.
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.
Wu, Yinghui (Silixa LLC) | Hull, Robert (Silixa LLC) | Tucker, Andrew (Apache Corp.) | Rice, Craig (Apache Corp.) | Richter, Peter (Silixa LLC) | Wygal, Ben (Silixa LLC) | Farhadiroushan, Mahmoud (Silixa Ltd.) | Trujillo, Kirk (Silixa LLC) | Woerpel, Craig (Silixa LLC)
Abstract Distributed fiber-optic sensing (DFOS) has been utilized in unconventional reservoirs for hydraulic fracture efficiency diagnostics for many years. Downhole fiber cables can be permanently installed external to the casing to monitor and measure the uniformity and efficiency of individual clusters and stages during the completion in the near-field wellbore environment. Ideally, a second fiber or multiple fibers can be deployed in offset well(s) to monitor and characterize fracture geometries recorded by fracture-driven interactions or frac-hits in the far-field. Fracture opening and closing, stress shadow creation and relaxation, along with stage isolation can be clearly identified. Most importantly, fracture propagation from the near to far-field can be better understood and correlated. With our current technology, we can deploy cost effective retrievable fibers to record these far-field data. Our objective here is to highlight key data that can be gathered with multiple fibers in a carefully planned well-spacing study and to evaluate and understand the correspondence between far-field and near-field Distributed Acoustic Sensing (DAS) data. In this paper, we present a case study of three adjacent horizontal wells equipped with fiber in the Permian basin. We can correlate the near-field fluid allocation across a stage down to the cluster level to far-field fracture driven interactions (FDIs) with their frac-hit strain intensity. With multiple fibers we can evaluate fracture geometry, the propagation of the hydraulic fractures, changes in the deformation related to completion designs, fracture complexity characterization and then integrate the results with other data to better understand the geomechanical processes between wells. Novel frac-hit corridor (FHC) is introduced to evaluate stage isolation, azimuth, and frac-hit intensity (FHI), which is measured in far-field. Frac design can be evaluated with the correlation from near-field allocation to far-field FHC and FHI. By analyzing multiple treatment and monitor wells, the correspondence can be further calibrated and examined. We observe the far-field FHC and FHI are directly related to the activities of near-field clusters and stages. A leaking plug may directly result in FHC overlapping, gaps and variations in FHI, which also can be correlated to cluster uniformity. A near-far field correspondence can be established to evaluate FHC and FHI behaviors. By utilizing various completion designs and related measurements (e.g. Distributed Temperature Sensing (DTS), gauges, microseismic etc.), optimization can be performed to change the frac design based on far-field and near-field DFOS data based on the Decision Tree Method (DTM). In summary, hydraulic fracture propagation can be better characterized, measured, and understood by deploying multiple fibers across a lease. The correspondence between the far-field measured FHC and FHI can be utilized for completion evaluation and diagnostics. As the observed strain is directly measured, completion engineering and geoscience teams can confidently optimize their understanding of the fracture designs in real-time.
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.
Huckabee, Paul (Shell Exploration & Production Co.) | Ledet, Chris (Shell Exploration & Production Co.) | Ugueto, Gustavo (Shell Exploration & Production Co.) | Tolle, John (Shell Exploration & Production Co.) | Mondal, Somnath (Shell Exploration & Production Co.)
Abstract This paper presents design considerations and field trial applications for determining practical dimensions and limits for interdependencies associated with stage length, perforation clusters and limited entry pressures. Recent applications by multiple authors and companies have begun to reverse the decade-long trend of reducing stage length and perforation spacing, in favor of extending stage lengths, to capture free cash flow value for unconventional resource development. Aggressive limited entry has been an enabler for successful extended stage length applications. Multiple authors have advocated "eXtreme Limited Entry" (XLE) applications. We present diagnostics data and applications that challenges the need for XLE and better constrains the necessary amount of limited entry pressures for effective stimulation distribution for resource development across multiple North American Basins. Data is presented from integrated application of field trials, stimulation distribution diagnostics, and well performance analysis. Field trials and well performance analysis are from the Permian Delaware Basin Wolfcamp. The field trials include both: greater perforation cluster intensities for base design stage lengths; and extended stage lengths of 50% greater than the base designs. Diagnostics are from multiple North American Basins and include discrete treatment pressure diagnostics and optic fiber distributed sensing. Data is presented to quantify the magnitude and variability for components necessary for maintaining active fracture extension for multiple perforation clusters. Components include: fracture breakdown pressures; in-situ stress, net fracture extension pressure, and near wellbore complexity pressure drop. Data and examples are presented from multiple wells, and resource development areas, to show the variability in measured treatment pressures for different length scale dimensions. This variability is used to determine the amount of limited entry pressure required to maintain fracture extension, dependent on the stage length dimension. Although Aggressive Limited Entry (ALE) is generally required to enable effective stimulation distribution and extended stage lengths in multiple cluster stages, examples are presented that demonstrate XLE is generally not required. We also discuss some of the considerations and observations that limit perforation cluster spacing intensities. Well performance data from the field trials is presented to validate the applications. This work demonstrates the value of integrated application of field trials, stimulation distribution diagnostics, and well performance analysis to capture free cash flow value from improved completions and stimulation designs. The discussion will include an assessment of future opportunities for further extension of stage length dimensions.
Abstract The subject of this paper is the application of a unique machine learning approach to the evaluation of Wolfcamp B completions. A database consisting of Reservoir, Completion, Frac and Production information from 301 Multi-Fractured Horizontal Wolfcamp B Completions was assembled. These completions were from a 10-County area located in the Texas portion of the Permian Basin. Within this database there is a wide variation in completion design from many operators; lateral lengths ranging from a low of about 4,000 ft to a high of almost 15,000 ft, proppant intensities from 500 to 4,000 lb/ft and frac stage spacing from 59 to 769 ft. Two independent self-organizing data mappings (SOM) were performed; the first on completion and frac stage parameters, the second on reservoir and geology. Characteristics for wells assigned to each SOM bin were determined. These two mappings were then combined into a reservoir type vs completion type matrix. This type of approach is intended to remove systemactic errors in measuement, bias and inconsistencies in the database so that more realistic assessments about well performance can be made. Production for completion and reservoir type combinations were determined. As a final step, a feed forward neural network (ANN) model was developed from the mapped data. This model was used to estimate Wolfcamp B production and economics for completion and frac designs. In the performance of this project, it became apparent that the incorporation of reservoir data was essential to understanding the impact of completion and frac design on multi-fractured horizontal Wolfcamp B well production and economic performance. As we would expect, wells with the most permeability, higher pore pressure, effective porosity and lower water saturation have the greatest potential for hydrocarbon production. The most effective completion types have an optimum combination of proppant intensity, fluid intensity, treatment rate, frac stage spacing and perforation clustering. This paper will be of interest to anyone optimizing hydraulically fractured Wolfcamp B completion design or evaluating Permian Basin prospects. Also, of interest is the impact of reservoir and completion characteristics such as permeability, porosity, water saturation, pressure, offset well production, proppant intensity, fluid intensity, frac stage spacing and lateral length on well production and economics. The methodology used to evaluate the impact of reservoir and completion parameters for this Wolfcamp project is unique and novel. In addition, compared to other methodologies, it is low cost and fast. And though the focus of this paper is on the Wolfcamp B Formation in the Midland Basin, this approach and workflow can be applied to any formation in any Basin, provided sufficient data is available.
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.
Ferrar, Joseph (DuPont Microbial Control) | Maun, Philip (DuPont Microbial Control) | Wunch, Kenneth (DuPont Microbial Control) | Moore, Joseph (DuPont Microbial Control) | Rajan, Jana (DuPont Microbial Control) | Raymond, Jon (DuPont Microbial Control) | Solomon, Ethan (DuPont Microbial Control) | Paschoalino, Matheus (DuPont Microbial Control)
Abstract We report the design, operation and biogenic souring data from a first-of-its kind suite of High Pressure, High Temperature (HPHT) Bioreactors for hydraulically fractured shale reservoirs. These bioreactors vet the ability of microbial control technologies, such as biocides, to prevent the onset of microbial contamination and reservoir souring at larger experimental volumes and higher pressures and temperatures than have been previously possible outside of field trials. The bioreactors were charged with proppant, crushed Permian shale, and sterile simulated fracturing fluids (SSFF). Subsets of bioreactors were charged with SSFF dosed with either no biocide, tributyl tetradecyl phosphonium chloride (TTPC, a cationic surface-active biocide), or 4,4-dimethyloxazolidine (DMO, a preservative biocide). The bioreactors were shut in under 1,000-2,500 psi and elevated temperatures for up to fifteen weeks; hydrogen sulfide (H2S) and microbial counts were measured approximately once per week, and additional microbes were introduced after weeks three and five. Across two separate studies, the bioreactors containing no biocide soured within the first week of shut-in and H2S concentrations increased rapidly beyond the maximum detectable level (343 ppm) within the first three to six weeks of shut-in. In the first study, the bioreactors treated with TTPC soured within two weeks of shut-in (prior to the first addition of fresh microbes), and H2S concentrations increased rapidly to nearly 200 ppm H2S within the first six weeks of shut-in and beyond the maximum detectable level after fifteen weeks of shut-in. The bioreactors containing DMO did not sour during either study until at least the first addition of fresh microbes, and higher levels of the preservative biocide continued to prevent the biogenic formation of H2S even during and after the addition of fresh microbes. Microbial counts correlate with the H2S readings across all bioreactor treatments. The differentiation in antimicrobial activity afforded by the different types of biocide treatments validates the use of these simulated laboratory reservoirs as a biocide selection tool. This first-of-its-kind suite of HPHT Bioreactors for hydraulic fracturing provides the most advanced biocide selection tool developed for the hydraulic fracturing industry to date. The bioreactors will guide completions and stimulation engineers in biocide program optimization under reservoir-relevant conditions prior to beginning lengthy and expensive field trials.
Ji, Qin (Reveal Energy Services) | Vernon, Geoff (Earthstone Energy) | Mata, Juan (Earthstone Energy) | Klier, Shannon (Earthstone Energy) | Perry, Matthew (Reveal Energy Services) | Garcia, Allie (Reveal Energy Services) | Coenen, Erica (Reveal Energy Services)
Abstract This paper demonstrates how to use pressure data from offset wells to assess fracture growth and evolution through each stage by quantifying the impacts of nearby parent well depletion, completion design, and formation. Production data is analyzed to understand the correlation between fracture geometries, well interactions, and well performance. The dataset in this project includes three child wells and one parent well, landed within two targets of the Wolfcamp B reservoir in the Midland Basin. The following workflow helped the operator understand the completion design effectiveness and its impact to production:Parent well pressure analysis during completion Isolated stage offset pressure analysis during completion One-month initial production analysis followed by one month shut-in Pressure interference test: sequentially bringing wells back online Production data comparison before and after shut-in period An integrated analysis of surface pressure data acquired from parent and offset child wells during completions provides an understanding of how hydraulic dimensions of each fracture stage are affected by fluid volume, proppant amount, frac stage order of operations, and nearby parent well depletion. Production data from all wells was analyzed to determine the impact of depletion on child well performance and to investigate the effects of varying completion designs. A pressure interference test based on Chow Pressure Group was also performed to further examine the connectivity between wells, both inter- and intra-zone. Surface pressure data recorded from isolated stages in the offset child wells during completions was used to resolve geometries and growth rates of the stimulated fractures. Asymmetric fracture growth, which preferentially propagates toward the depleted rock volume around the parent well, was identified at the heel of the child well closest to the parent. Fracture geometries of various child well stage groups were analyzed to determine the effectiveness of different completion designs and the impact of in situ formation properties. Analysis of parent well surface pressure data indicates that changing the completion design effectively reduced the magnitude of Fracture Driven Interactions (FDIs) between child and parent wells. Child well production was negatively impacted in the wells where the fracture boundary overlapped with the parent well depleted volume in the same formation zone. This study combines pressure and production analyses to better understand inter- and intra-zone interference between wells. The demonstrated workflow offers a very cost-effective approach to studying well interference. Observing and understanding the factors that drive fracture growth behavior enables better decision-making during completion design planning, mitigation of parent-child communication, and enhancement of offset well production.
Abstract Well spacing and stimulation design are amongst the highest impact design variables which can dictate the economics of an unconventional development. The objective of this paper is to showcase a numerical simulation workflow, with emphasis on the hydraulic fracture simulation methodology, which optimizes well spacing and completion design simultaneously. The workflow is deployed using Cloud Computing functionality, a step-change over past simulation methods. Workflow showcased in this paper covers the whole cycle of 1) petrophysical and geomechanical modeling, 2) hydraulic fracture simulations and 3) reservoir simulation modeling, followed by 4) design optimization using advanced non-linear methods. The focus of this paper is to discuss the hydraulic fracture simulation methods which are an integral part of this workflow. The workflow is deployed on a dataset from a multi-well pad completed in late 2018 targeting two landing zones in the Vaca Muerta shale play. On calibrated petrophysical and geomechanical model, hydraulic fracture simulations are conducted to map the stimulated rock around the wellbores. Finely gridded base model is utilized to capture the property variation between layers to estimate fracture height. The 3d discrete fracture network (DFN) built for the acreage is utilized to pick the natural fracture characteristics of the layers intersected by the wellbores. The methodology highlights advances over the past modeling approaches by including the variation of discrete fracture network between layers. The hydraulic fracture model in conjunction with reservoir flow simulation is used for history matching the production data. On the history matched model, a design of experiments (DOE) simulation study is conducted to quantify the impact of a wide range of well spacing and stimulation design variables. These simulations are facilitated by the recent deployments of cloud computing. Cloud computing allows parallel running of hundreds of hydraulic fracturing and reservoir simulations, thereby allowing testing of many combinations of stimulation deigns and well spacing and reducing the effective run time from 3 months on a local machine to 1 week on the cloud. Output from the parallel simulations are fitted with a proxy model to finally select the well spacing and stimulation design variables that offer the minimum unit development cost i.e. capital cost-$ per EUR-bbl. The workflow illustrates that stimulation design and well spacing are interlinked to each other and need to be optimized simultaneously to maximize the economics of an unconventional asset. Using the workflow, the team identified development designs which increase EUR of a development area by 50-100% and reduce the unit development cost ($/bbl-EUR) by 10-30%.