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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.
Dontsov, Egor (ResFrac Corporation) | Suarez-Rivera, Roberto (W. D. Von Gonten Laboratories) | Panse, Rohit (W. D. Von Gonten Laboratories) | Quinn, Christopher (W. D. Von Gonten Laboratories) | LaReau, Heather (BP America Production Company, BPx Energy Inc.) | Suter, Kirke (BP America Production Company, BPx Energy Inc.) | Hines, Chris (BP America Production Company, BPx Energy Inc.) | Montgomery, Ryan (BP America Production Company, BPx Energy Inc.) | Koontz, Kyle (BP America Production Company, BPx Energy Inc.)
Abstract As the number of wells drilled in regions with existing producing wells increases, understanding the detrimental impact of these by the depleted zone around parent wells becomes more urgent and important. This understanding should include being able to predict the extent and heterogeneity of the depleted region near the pre-existing wells, the resulting altered stress field, and the effect of this on newly created fractures from adjacent child wells. In this paper we present a workflow that addresses the above concern in the Eagle Ford shale play, using numerical simulations of fracturing and reservoir flow, to define the effect of the depletion zone on child wells and match their field production data. We utilize an ultra-fast hydraulic fracture and depletion model to conduct several hundred numerical simulations, with varying values of permeability and surface area, seeking for cases that match the field production data. Multiple solutions exist that match the field data equally well, and we used additional field production data of parent-child well-interaction, to select the most plausible model. Results show that the depletion zone is strongly non-uniform and that large reservoir regions remain undepleted. We observe two important effects of the depleted zone on fractures from child wells drilled adjacent to the parents. Some fractures propagate towards low pressure zones and do not contribute to production. Others are repelled by the higher stress region that develops around the depletion zone, propagate into undepleted rock, and have production rates commensurate to that from other child wells drilled away from depleted region. The observations are validated by the field data. Results are being used to optimize well placement and well spacing for subsequent field operations, with the objective to increase the effectiveness of the child wells.
Abstract Stage length and perforation cluster spacing are important design parameters for multi-stage hydraulic fracturing. This study aims to demonstrate that the interplay between subtle variations of the least principal stress (Shmin) with depth and the stress shadows induced by simultaneously propagating hydraulic fractures from multiple perforation clusters, primarily determines the propped and fractured area in the target formations. This principle is illustrated with the help of a case study in a prolific unconventional formation in the north eastern US, where the vertical stress variations are well characterized through discrete multi-depth stress measurements and actual stage design parameters used by the operator are known. At first, we show how the hydraulic fracture footprint and proppant distribution varies with a change in the vertical stress profile. The stress profile is shown to be a very important in determining the optimal vertical and lateral well spacing. The evolution of the stress shadow in the different layers is shown during the pumping as the fracture propagates across multiple layer boundaries. Subsequently, we demonstrate that by changing the magnitude of stress perturbations caused by the stress shadow effect, the distribution of propped area can be altered significantly. We use this method to determine the optimal cluster spacing keeping other design parameters constant such as flow rate, perforation diameter, etc. Simulations from selected cluster spacing realizations are run with high and low permeability scenarios to show the importance of correct matrix permeability inputs in determining the three-dimensional depletion profile and ultimate production. By varying the cluster spacing we show the hydraulic fracture propagation change from being solely stress layering driven to stress shadow influenced. The effect of stress shadow on the final fracture footprint is highly specific depending on the given stress layering and is thus case-dependent. This study demonstrates that knowledge of stress variations with depth and modeling are critical for optimizing stimulation efficiency.
We use a high-quality dataset in the Bakken Shale to calibrate a numerical model to a complex and diverse set of parent/child observations. Two vertical wells (V1 and V2) were drilled 1000 ft and 1200 ft away from a legacy well with 10 years of production, H1. A DFIT was performed in the V1, followed by a 24 hour low-rate injection in the H1 (a microseismic depletion delineation, MDD, test). Subsequently, a small frac job was performed in the V1, followed by DFITs in the V1 and V2. The dataset yields a diversity of data to calibrate a numerical model: historical production of the H1, pressure response in the H1 from the MDD injection and the V1 fracture treatment, production rate uplift in the H1 following the V1 frac, microseismic, and pressure response during the three DFITs. The entire dataset was history matched in a single continuous simulation with a numerical simulator that fully integrates hydraulic fracture and reservoir simulation. The simulation was set up to closely match a geologic model that was built in prior work. The integrated simulation allows simulation of the fractures reopening around the H1 as a consequence of the MDD, the transport of proppant from the V1 to the H1 well, and the subsequent communication and poroelastic stress response. The Biot coefficient was calibrated to match the observed change in stress at the H1 well after ten years of depletion. The fracture toughness was calibrated to match the observed fracture geometry from the microseismic around the V1 well during fracturing. A proppant transport parameter called ‘maximum immobilized proppant’ was tuned to the production and DFIT data. The match to the V2 DFIT suggests that it is not directly in contact with the V1 fracture, even though the wells are relatively close together along fracture strike. The initial V1 DFIT suggests that it has, at most, weak contact with the H1. The second V1 DFIT, performed after the fracturing treatment, demonstrates communication with the H1, and consequently, depletion. The observations demonstrate that the H1 was able to produce from the previously undepleted rock around the V1, even though it was 1000 ft away. Overall, the results indicate that Bakken wells can achieve substantial (at least 1000 ft) effective half-length, that frac hits on parent wells in the Bakken do not necessarily result in production degradation and can even increase production, that the apparent Biot coefficient is relatively low (∼0.34), that the amount of proppant trapping due to localized screenout is relatively low (but nonzero), and this entire, complex dataset can be explained using a planar fracture modeling approach.
McClure, Mark (ResFrac Corporation) | Picone, Matteo (ResFrac Corporation) | Fowler, Garrett (ResFrac Corporation) | Ratcliff, Dave (ResFrac Corporation) | Kang, Charles (ResFrac Corporation) | Medam, Soma (ResFrac Corporation) | Frantz, Joe (ResFrac Corporation)
Abstract Hydraulic fracturing and reservoir simulation are used by operators in shale to optimize design parameters such as well spacing, cluster spacing, and injection schedule. In this paper, we address ‘freqently asked questions’ that we encounter when working on hydraulic fracture modeling projects with operators. First, we discuss three high-level topics: (1) data-driven and physics-based models, (2) the modeling workflow, and (3) planar-fracture modeling versus ‘complex fracture network’ modeling. Next, we address specific technical topics related to modeling and the overall physics of hydraulic fracturing: (1) interrelationships between cluster spacing and other design parameters, (2) processes affecting fracture size, (3) fracture symmetry/asymmetry, (4) proppant settling versus trapping, (5) applications of Rate-Transient Analysis (RTA), (6) net pressure matching, (7) Initial Shut-In Pressure (ISIP) trends along the wellbore, and (8) the effect of understressed/underpressured layers. We discuss practical modeling decisions in the context of field observations.
Abstract Maximizing economic performance in shale requires optimal selection of well and cluster spacing, among other parameters. Reservoir engineering calculations can be used to optimize spacing, but these calculations are impacted by uncertainties in input parameters. System permeability is particularly important and difficult to measure. Diagnostic Fracture Injection Tests (DFIT's) are often used to estimate permeability because they provide a direct, in-situ measurement. However, in recent work, it was shown that conventional DFIT interpretation techniques can overestimate permeability in gas shale by two orders of magnitude. In this study, the impact of the permeability estimate is demonstrated using a dataset from the Utica/Point Pleasant. Production data is history matched with models assuming high and low permeability. It is possible to history match both models because of non-uniqueness between fracture area and permeability. Sensitivity analysis simulations are performed to assess the impact of well and cluster spacing on net present value. Relative to the high permeability model, the low permeability model has a greater optimal well spacing and a tighter optimal cluster spacing. The comparison shows that improved accuracy in the permeability estimate significantly improves economic performance. The low permeability model has much earlier production interference than the high permeability model because the low permeability model requires greater effective fracture length to match production. This is consistent with the operator's experience that outer wells outproduce inner wells within weeks or months from the start of production.
Maximizing economic performance in shale requires optimal selection of well and cluster spacing, among other parameters. Reservoir engineering calculations can be used to optimize spacing, but these calculations are impacted by uncertainties in input parameters. System permeability is particularly important and difficult to measure. Diagnostic Fracture Injection Tests (DFIT's) are often used to estimate permeability because they provide a direct, in-situ measurement. However, in recent work, it was shown that conventional DFIT interpretation techniques can overestimate permeability in gas shale by two orders of magnitude. In this study, the impact of the permeability estimate is demonstrated using a dataset from the Utica/Point Pleasant. Production data is history matched with models assuming high and low permeability. It is possible to history match both models because of non-uniqueness between fracture area and permeability. Sensitivity analysis simulations are performed to assess the impact of well and cluster spacing on net present value. Relative to the high permeability model, the low permeability model has a greater optimal well spacing and a tighter optimal cluster spacing. The comparison shows that improved accuracy in the permeability estimate significantly improves economic performance. The low permeability model has much earlier production interference than the high permeability model because the low permeability model requires greater effective fracture length to match production. This is consistent with the operator's experience that outer wells outproduce inner wells within weeks or months from the start of production.
McClure, Mark (ResFrac Corporation) | Bammidi, Vidya (Keane Group) | Cipolla, Craig (Hess Corporation) | Cramer, Dave (ConocoPhillips Company) | Martin, Lucas (Formerly with Apache Corporation, now with Marathon Oil Company) | Savitski, Alexei (Shell International Exploration and Production Inc.) | Sobernheim, Dave (Keane Group) | Voller, Kate (Range Resources Corporation)
Abstract This paper summarizes findings from a one-year study sponsored by seven operators and service companies to investigate interpretation of diagnostic fracture injection tests (DFIT’s). The study combined computational modeling, a diverse collection of field data, and operator experience. DFIT simulations were performed with a three-dimensional hydraulic fracturing, wellbore, and reservoir simulator that describes fracture propagation, contacting of the fracture walls, and multiphase flow. Interpretation procedures were applied to estimate stress, permeability, and pressure from the synthetic data. The interpretations were compared to the simulation input parameters to evaluate accuracy. Based on the results, new techniques were developed, existing techniques were refined, and an overall interpretation protocol was developed. The techniques were applied to interpret over thirty field DFIT’s drawn from shale plays across the US and Canada, and the methods were evaluated in the context of operator experience. The results are applicable to fracturing tests in formations with permeability ranging from nanodarcies to 10s of microdarcies. The minimum principal stress is estimated by identifying the ‘contact pressure’ when the fracture walls come into contact, causing fracture compliance and system storage coefficient to decrease. After the walls come into contact, the pressure transient is controlled by the interplay of changing fracture compliance, deviation from Carter leakoff, and multiphase flow. The contact pressure is slightly greater than the minimum principal stress. It can be identified from either a plot of dP/dG or a relative stiffness plot. Permeability is estimated using the G-function method, a newly developed h-function method that accounts for deviation from Carter leakoff, and impulse linear flow. These three methods, which are based on linear flow geometry, require an estimate of fracture area. We derive equations for estimating area using mass balance equations, accounting for wellbore storage and fluid leakoff. The results from field data show that impulse linear permeability estimates are usually 2-5 times lower than estimates derived from the G-function and h-function methods, apparently indicating a difference between effective permeability during leakoff and permeability during flow of reservoir fluid through the formation. Impulse radial flow regime may be used for estimating permeability, but should be used with caution. Simulation results indicate that a variety of processes can cause an apparent radial trend that is not actually radial flow. Simulations and field data indicate that ‘false radial’ is very common in gas reservoirs and, if applied, leads to a large overestimate of permeability. Production history matching using overestimated permeability will underestimate fracture length, potentially resulting in suboptimal choices for well and cluster spacing.
Abstract Tank-style development in the thick Spraberry-Wolfcamp sequence in the Midland Basin offers a variety of operational efficiency gains which directly translate into cost savings for the operator who has the foresight to plan their acreage development in this manner. Simultaneous development of multiple stacked pay zones presents a technical challenge to maximize production from each zone and the value of the entire DSU, while achieving cost savings, as appropriate. Optimizing completions in tank-style development in a multi-zone pay system is conducted through a combination of well experiments, field trials, and numerical modeling. Using longer stages allows an operator to increase the pace at which wells are completed and translates directly into cost savings. Completing two wells at once further accelerates development, but surface equipment capabilities must be considered if maximum pump rate per well is restricted. Balancing this reduced pump rate with limited-entry can be used to maximize cluster efficiency and the likelihood that hydraulic fractures propagate from each perforation cluster in a stage. Data from RA tracers and step-down tests show the effectiveness of limited-entry on maximizing cluster efficiency. Hydraulic fracture modeling provides insight into the development of competing fractures during the completions operations. Field observations from RA tracers and step-down tests show that the limited-entry approach of reducing shots-per-foot and perforation diameter and focusing on perforation friction pressure instead of total rate leads to equally effective stimulation in a more operationally efficient manner. Hydraulic fracture modeling supports how limited-entry can be used to effectively stimulate longer stages and complete at lower pump rates by optimizing perforation friction pressure. Hydraulic fracture modeling also shows the impact of stress shadowing on hydraulic fracture geometry of different designs in stacked field development. Forward modeling of production from the hydraulic fracture models allows quantification of the value of the operational efficiency gains. This work will highlight how one operator worked to balance optimal fracture design with operational efficiency to maximize the value of a DSU in a stacked, tank-style development. This presentation integrates field and well level completion results, historical stage-level data analytics, and forward modeling of hydraulic fracturing and production in a coupled numerical simulator.
Abstract This paper presents an analysis of the interactions between stimulation design and two important geomechanical effects: the variation of least principal stress (Shmin) between lithological layers and the stress shadow effect that arises from simultaneously propagating adjacent hydraulic fractures. To demonstrate these interactions, hydraulic fracture propagation is modeled with a 5-layer geomechanical model representing an actual case study. The model consists of a profile of Shmin measurements made within, below and above the producing interval. The stress variations between layers leads to an overall upward fracture propagation and proppant largely above the producing interval. This is due to interactions between the pressure distribution within the fracture and the stress contrast in the multiple layers. A sensitivity study is done to investigate the complex 3-D couplings between geomechanical constraints and well completion design parameters such as landing zone, cluster spacing, perforation diameter, flow rate and proppant concentration. The simulation results demonstrate the importance of a well characterized stress stratigraphy for prediction of hydraulic fracture characteristics and optimization of operational parameters.