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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.
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.
Summary We propose a novel method for estimating average fracture compressibility during flowback process and apply it to flowback data from 10 multifractured horizontal wells completed in Woodford (WF) and Meramec (MM) formations. We conduct complementary diagnostic flow-regime analyses and calculate by combining a flowing-material-balance (FMB) equation with pressure-normalized-rate (PNR)-decline analysis. Flowback data of these wells show up to 2 weeks of single-phase water production followed by hydrocarbon breakthrough. Plots of water-rate-normalized pressure and its derivative show pronounced unit slopes, suggesting boundary-dominated flow (BDF) of water in fractures during single-phase flow. Water PNR decline curves follow a harmonic trend during single-phase- and multiphase-flow periods. Ultimate water production from the forecasted harmonic trend gives an estimate of initial fracture volume. The estimates for these wells are verified by comparing them with the ones from the Aguilera (1999) type curves for natural fractures and experimental data. The results show that our estimates (4 to 22×10psi) are close to the lower limit of the values estimated by previous studies, which can be explained by the presence of proppants in hydraulic fractures.
Zhang, Zhenzihao (University of Calgary) | Clarkson, Christopher (University of Calgary) | Williams-Kovacs, Jesse D. (University of Calgary and Sproule Associates) | Yuan, Bin (University of Calgary) | Ghanizadeh, Amin (University of Calgary)
Summary The application of rate‐transient‐analysis (RTA) concepts to flowback data gathered from multifractured horizontal wells (MFHWs) completed in tight/shale reservoirs has recently been proposed as an independent method for quantitatively evaluating hydraulic‐fracture volume/conductivity. However, the initial fluid pressures and saturation in the fracture network and adjacent reservoir matrix are generally unknown at the start of flowback, creating significant uncertainty in the quantitative analysis of flowback data. In this study, we present a semianalytical flow model, coupled with a hydraulic‐fracture (fracture) model and constrained with laboratory‐based geomechanical data, for evaluating the initial conditions of flowback. In previous work, a semianalytical model based on the dynamic‐drainage‐area (DDA) concept was used to simulate water‐based fluid leakoff from an MFHW into a tight oil reservoir (Montney Formation, western Canada), with minimal mobile water, during and after fracturing operations. The model assumed that each fracturing stage can be represented by a primary hydraulic fracture (PHF) containing the majority of the proppant, and an adjacent nonstimulated reservoir (NSR) or enhanced fracture region (EFR), which is an area of elevated permeability in the reservoir caused by the stimulation treatment. Each region was represented by a single‐porosity system. The DDA propagation speed within the PHF during the stimulation treatment was constrained through using a simple analytical fracture model. Although this approach was considered novel, several improvements and additional laboratory constraints were considered necessary to yield more accurate predictions of initial flowback conditions. In the current work, the modeling approach described previously was improved by representing the EFR with a dual‐porosity system; fully coupling the fracture model (used for PHF creation and propagation) with the DDA model for fluid‐leakoff simulation into the EFR and adding a proppant‐transport model; and modeling the shut‐in period. Finally, to ensure that model geomechanics were properly constrained, a comprehensive suite of previously gathered laboratory data was used. Laboratory‐derived propped (PHF) and unpropped (EFR) fracture‐permeability/conductivity data as a function of pore pressure, as well as fracture‐compressibility data, were used as constraints for the model. It should be noted that our model assumes that fracture closure has no effect on the pressure/saturation of the PHF/EFR/matrix. The improved model was reapplied to the tight oil field case and yielded more realistic estimates of initial flowback conditions, enabling more confident history matching of flowback data. The results of this study will be important to those petroleum engineers interested in quantitative analysis of flowback data to accurately obtain fracture properties by ensuring proper model creation.
Abstract Injection Fall-Off (IFO) testing is one of the most important methods to help monitor injector performance over time in waterfloods, water disposal operations, polymer floods, etc. IFO tests provide information about, amongst others, k*h, skin, reservoir transmissibility, and mobility contrasts. Analysis of the early-time period of such tests also can yield estimates of length and height of fractures that are induced during injection. There is however, one important parameter that cannot be estimated from IFO tests, which is the Fracture Closure Pressure (FCP) which is generally considered to be a measure for minimum principal in-situ stress. In this work, we present exact 3D simulations of hydraulic fracture propagation, followed by fracture closure as a result of shut-in and after-closure reservoir flow. The simulations focus on the details of valve closure at the wellhead followed by propagation and (repeated) reflection of the closure-induced pressure pulse (‘water hammer’) whilst at the same time the fracture is gradually closing. The simulated post shut-in pressure decline trends which are the combined result of water hammer, fracture closure and reservoir fluid flow have been compared with field data. The main result that consistently emerged from our simulations and their comparison with field data is that the water hammer disappears as soon as the fracture is completely closed. This can be explained by the fact that the magnitude of a water hammer following injector shut-in strongly increases with the total ‘system’ (wellbore plus fracture) compliance (storage), as is evidenced from our simulations. Since often, the system compliance for an open fracture is an order of magnitude higher than for a closed fracture, fracture closure itself results in a practical disappearance of water hammer. Thus, identification of the point of water hammer disappearance after shut-in allows one to estimate FCP.
Johnson, Raymond L. (University of Queensland) | You, Zhenjiang (University of Queensland) | Ribeiro, Ayrton (University of Queensland) | Mukherjee, Saswata (University of Queensland) | Salomao de Santiago, Vanessa (University of Queensland) | Leonardi, Christopher (University of Queensland)
Defining pressure dependent permeability (PDP) behaviour in coalbed methane (CBM) or coal seam gas (CSG) reservoirs using reservoir simulation is non-unique based on the uncertainty in coal properties and input parameters. A diagnostic fracture injection test (DFIT) can be used to investigate bulk permeability at a reservoir level and at lowered net effective stress conditions. As coal has minimal matrix porosity and under DFIT conditions cleat porosity is fluid saturated with reasonably definable total compressibility values, the DFIT data can provide insight into PDP parameters. At pressures above the fissure opening pressure, pressure dependent leak off (PDL) behaviour increases exponentially with increasing pressure. Many authors have noted that with decreasing pressure PDP declines exponentially with increasing net effective stress. Thus, PDP behaviour can be defined by PDL.
In this paper, we show how combined analyses, using typically collected field data, can be used to better define and constrain the modelling of PDP. We illustrate this process based on a well case study that includes the following data: fracture fabric and porosity reasonably defined from image log and areal core studies; DFIT data acquired under initial saturation conditions; hydraulic fracturing data; and longer term production data. These analyses will be integrated and used to constrain the parameters required to obtain a rate and pressure history-match from the post-frac well production data.
This workflow has application in other coal seam gas cases by identifying key variables where hydraulic fracturing performance has been unable to overcome limitations based on pressure or stress dependent behaviours and often accompanied by low reservoir permeability values. While this is purposely targeting areas where only typically collected field data is available, this workflow can include coal testing data for matrix swelling/shrinkage properties or other production data analysis techniques.