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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.
Abstract The presence of natural fractures in hydraulic fracturing candidates can present an array of well completion problems. Natural fractures can be very difficult if not impossible to model without adequate pre-job diagnostic testing to calibrate simulation. Left undetected natural fractures can cause premature screen-out as well as formation damage. In tight gas sand formations, natural fractures can be the predominate production mechanism in the reservoir. If polymer residue is left in the natural fractures after drilling, stimulation or work-over, a substantial amount of potential production may be left behind. Often this type of damage may be documented by the sheer fact that production may decrease after these types of operations. Techniques have been perfected to determine the impact on leakoff due to natural fractures. In many cases production may exceed the predictive capability of production simulators without the introduction of permeability numbers that might be considered high for that area. This could lead one to believe that some portion of the production is dominated by natural fractures. A better understanding this type of leakoff could help in the development of methods to predict production results or economics of a well based on pre-job testing. It is the intention of this paper to discuss methodology to predict the presence of natural fractures and show key considerations when trying to simulate their behavior. This paper will also investigate stimulation problems and damage mechanisms, describing methods that may be used to help minimize their impact. An earlier version of this paper was presented by this author at the Forty-Sixth Annual Southwest Petroleum Short Course April 21–22, 1999. Introduction Naturally occurring fractures in petroleum and gas bearing reservoirs can present a number of completion and design challenges. The number one problem in stimulating these types of reservoirs is the unpredictive nature surrounding these phenomena. Advanced Stimulation Technology (AST) introduced by the Gas Research Institute (GRI) in the early 90's formed the groundwork that presented methodology that would prove instrumental in developing techniques to help characterize the challenges encountered in the design and analysis of hydraulic fracturing treatments in tight gas sands. These techniques have proven invaluable in developing a systematic method to evaluate the complex issues encountered when modeling. A number of key considerations must be examined to help insure optimum success when modeling natural fractures. The number one concern is developing criterion that will aid in predicting the existence and magnitude of naturally fractured systems. Before any attempt at developing an accurate design can be achieved, methodology must be developed to aid in the prediction of natural fractures. The next major concern is to develop a stimulation technique that will achieve the desired results and optimize the treatment. Based on the evolution of AST many tool kits have been developed to aid in this task. These tool kits may consist of a series of computer programs or spreadsheets that employ various techniques designed to assist in the expedient implementation of this design methodology. Many of these tool kits are commercially available, while others may be considered proprietary in nature and therefore may not be readily available except for exclusive use by the developer company, but adequate literature exists to develop these tool kits on your own if desired. A third concern is the all-encompassing damage issue. In naturally fractured systems a major portion of production can originate from these fractures. If the stimulation treatment damages this natural fracture network, then post frac production can be compromised or actually decrease. New technologies exist to help minimize this type of damage.