Summary This study is a comparison of hydraulic fracture models run using test data from the GRI Staged Field Experiment No. 3. Models compared include 2D, pseudo-3D, and 3D codes, run on up to eight different cases. Documented in this comparison are the differences in length, height, width, pressure, and efficiency. The purpose of this study is to provide the completions engineer with a practical comparison of the available models so that rational decisions can be made as to which model is optimal for a given application. Introduction Hydraulic fracturing, one of the most important stimulation techniques available to the petroleum engineer, is being used extensively in tight gas sandstones,1–5 coalbed methane,6 high-permeability sandstones in Alaska,7very weak sandstones off the U.S. gulf coast,8horizontal wells in chalks,9–10 and many other applications from waste disposal to geothermal reservoirs. Because of this diversity of application, hydraulic fracture design models must be able to account for widely varying rock properties, reservoir properties, in-situ stresses, fracturing fluids, and proppant loads. As a result, fracture simulation has emerged as a highly complex endeavor that must be able to account for many different physical processes. The petroleum engineer who must design the fracture treatment is often confronted with the difficult task of selecting a suitable hydraulic fracture model, yet there is very little comparative information available to help in making a rational choice, particularly on the newer 3D and pseudo-3D models. The purpose of this paper is to help provide some guidance by comparing many of the available simulators. The Fracture Propagation Modeling Forum held Feb. 26-27, 1991, near Houston provided the origin for this paper. This forum, sponsored by the Gas Research Inst. (GRI), was open to all known hydraulic fracturing modelers. Participants were asked to provide fracture designs based on the Staged Field Experiment (SFE) No. 3 fracture experiment. After the fracture designs presented at this meeting were compared, a final, revised data set was given to all participants. The results presented in this paper are derived from that data set. To publish the results, a four-member committee (the authors) was chosen from forum participants. In assembling this comparison, committee members purposely attempted to avoid judging the relative values of the different models. Only the results and quantifiable comparisons are given. Background—Basic Modeling Discussion In recent years, fracturing simulators used in the oil industry have proliferated. This proliferation was intensified by the availability of personal computers and the need for fast design simulators for use in the field. Applying these models as "black boxes," without knowledge of the underlying assumptions, may lead to erroneous conclusions, especially for unconfined fracture growth. Hydraulic fracturing is a complex nonlinear mathematical problem that involves the mechanical interaction of the propagating fracture with the injected slurry. Several assumptions are commonly made to render the problem tractable:plane fractures, symmetric with respect to the wellbore; elastic formation;linear fracture mechanics for fracture propagation prediction; power-law behavior of fracturing fluids and slurries; simplification of fracture geometry and its representation by few geometric parameters; etc. Ref. 11 gives a detailed description of the governing equations. Although the models predict "trends" of treating pressure behavior, they may not always reliably predict the observed behavior for a given treatment. This discrepancy has been attributed to many complex interactions between the injected fluids and the formation that are not well understood. An attempt to characterize phenomenologically some of these complex processes occurring within the fracture (e.g., multiple fractures and increasted frictional losses) and near the fracture tip (e.g., nonlinear formation behavior, microcracking, formation plasticity, dilatancy, and plugging) was made in various simulators by the introduction of additional ad hoc parameters ("knobs"). The choice of values for these parameters is based only on the modeler's experience. These knobs, used to match model predictions with field-observed behavior, result in the lack of a standard model response for a given physical problem. This issue was addressed in the forum by having different participants (discussing several different models) simulate common test cases derived from the actual SFE No.3 fracturing treatment. These models can be categorized in order of decreasing complexity as follows.Planar 3D models: TerraFrac of TerraTek Inc.12-16 run by Arco and HYFRAC3D by S.H. Advani of Lehigh U.17GOHFER, a unique finite-difference simulator by Marathon Oil Co.18,19Planar pseudo-3D models."Cell" approach: STIMPLAN of NSI Inc., ENERFRAC of Shell20,21 and TRIFAC of S.A. Holditch& Assocs. Inc.Overall fracture geometry parameterization: FRACPRO of Reservoir Engineering Systems (RES) Inc.22-25and MFRAC-ll of Meyer & Assocs.26-29Classic Perkins-Kern-Nordgren (PKN) and Geertsma-deKlerk(GDK) models30-35: PROP of Halliburton,34-36 the Chevron 2D model, the Conoco 2D model, the Shell 2D model, and pseudo-3D models run in constant-height mode. A discussion of the basics of these models is given to provide some insights on the model assumptions and their expected effect on results. Planar 3D Models. The TerraFrac12–16 and the HYFRAC3D17 models incorporate similar assumptions and formulate the physics rigorously, assuming planar fractures of arbitrary shape in a linearly elastic formation, 2D flow in the fracture, power-law fluids, and linear fracture mechanics for fracture propagation. Their difference is in the numerical technique used to calculate fracture opening. TerraFrac uses an integral equation representation, while the Ohio State model uses the finite-element method. Both models use finite elements for 2D fluid flow within the fracture and a fracture-tip advancement proportional to the stress-intensity factor on the fracture-tip contour. Planar 3D Models. The TerraFrac12–16 and the HYFRAC3D17 models incorporate similar assumptions and formulate the physics rigorously, assuming planar fractures of arbitrary shape in a linearly elastic formation, 2D flow in the fracture, power-law fluids, and linear fracture mechanics for fracture propagation. Their difference is in the numerical technique used to calculate fracture opening. TerraFrac uses an integral equation representation, while the Ohio State model uses the finite-element method. Both models use finite elements for 2D fluid flow within the fracture and a fracture-tip advancement proportional to the stress-intensity factor on the fracture-tip contour.

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Production from shale gas reservoirs in the USA has become an important component in the increase of natural gas supply. The Haynesville shale, in particular, is a major contributor in gas supply due mainly to its relatively higher initial deliverability compared to other gas shale plays. One of the critical questions in developing a play efficiently and economically is the well spacing. There are several approaches to addressing this question. The paper looks at one approach, namely the process behind building a calibrated, history matched multi well reservoir model. The model is run in prediction mode with different sensitivities to answer the well spacing issue. The model honors the initial static and dynamic conditions, is capable of running in a reasonable time and, most importantly, has been useful to management in the decision making process. In this field case, a half section in the state of Louisiana has been drilled and completed with 4 horizontal multistage producing wells and 2 vertical microseismic monitoring wells, 1 of which was subsequently converted to a downhole pressure monitoring well. During the entire hydraulic fracturing operation, downhole microseismic data were simultaneously recorded in both observation wells. The pressure data from the monitor well acquired during production was entered into the reservoir model as another history matching variable. The microseismic data were used to calculate the fracture parameters and as a limiting constraint in the process. This dual porosity model is a practical example application of the methodology previously described in SPE paper 132180 by Du et al. (2010). The sections in this paper describe a method for building a reservoir model that honors the static boundary conditions. The model was built in two parts according to the Dual Porosity nature of it: a conventional geological model representing the initial porosity and permeability of the rock matrix, and a second part that models the fracture network generated by the stimulation operations and the pre-existing natural fractures. The paper then explains how this model was tuned to enable a production and pressure history match. There is also a section devoted to the generation and utilization of a critical correlation between pressure depletion and a combined fracture half-length times the square root of permeability (Xf.√k) parameter which greatly reduced the uncertainty caused by the non-uniqueness of the match. Finally, some general conclusions regarding the results are presented.

While well interference is a known phenomenon in shale gas plays, it is often overlooked or only considered when its effects are readily apparent. Spacing tests are often performed when starting to appraise or develop a new area where a qualitative evaluation of interference between drilled wells will determine the appropriate well spacing. While numerical reservoir modelling and build-up analysis can be applied in the Marcellus shale play they are not appropriate for determining optimal spacing due to very low, nano-darcy reservoir permeabilities and uncertainty over hydraulic fracture geometry. The challenge was to develop a new approach to measure and estimate the impact of interference on gas recovery and optimize well spacing. The impact of interference was initially evaluated by assessing the change in the productivity index of wells due to offset wells being added, put on production or shut/in. In order to have a more meaningful way of estimating its impacts on economics, interference was also quantified based on projected future five year cumulative production using Arps decline curve, Rate Transient Analysis and Pressure Normalized Rate methods. Results were compared and a statistical workflow was used to estimate optimal spacing. By relating the degree of interference with overlap between wells, the nature of interference was also investigated. Interference can be due to a Stimulated Rock Volume (SRV) overlap. This is characterized by a proportionality increasing interference with SRV overlap. The impact of natural features such as faults or high permeability streaks that can act as conductivity highways across many wells is usually not proportional to overlap. This study in Marcellus shale play demonstrated that measurable interference occurred at wide spacing and that 1,000 ft spacing should result in an increased FYFCP (Five Year Forecasted Cumulative Production) of 10% over existing spacing assumptions, key at low gas prices. Therefore, 1,000 ft spacing has been recommended for future well placement. The workflow outlined in this paper is currently being used to evaluate well spacing for other assets and can be used by Reservoir Engineers to evaluate spacing in tight or shale gas/oil plays.

Previously, ExxonMobil had undertaken a multi-disciplinary approach to develop and integrate the required technologies for design, implementation, and evaluation of acid treatments in thick heterogeneous carbonate reservoirs.1 RasGas, in collaboration with ExxonMobil, has customized the technologies and integrated methodology for application in a major field in the Middle East with a high level of success. Acid placement and diversion are critical to achieving effective stimulation in heterogeneous carbonate reservoirs. While permeability is a major factor in the distribution of acid along a completion for many reservoirs, pre-stimulation skin damage, intermixed rock types with different acid-rock wormholing characteristics, distance between zones, and differential reservoir depletion also play important roles in the effective stimulation of the reservoirs. Important steps in the integrated methodology developed and implemented for matrix acidizing include:determine the stimulation requirements given the well/reservoir objectives,characterize the various rock types present in the formation,develop an integrated perforation/stimulation strategy,conduct appropriate laboratory tests with representative field core plugs,model the stimulation process with tools calibrated to the formation of interest,develop field procedures and implement the treatments as per design,evaluate stimulation effectiveness, andoptimize treatments based on post-stimulation performance and operational constraints. This paper features some of the technologies that have been developed and describes the integrated methodology used to effectively stimulate thick carbonate reservoirs in the Middle East. Introduction The technology of carbonate matrix stimulation has advanced significantly over the past 10 years through innovative laboratory testing, new fluid developments, and advanced computer models to simulate the process. However, the existing approaches are not sufficient to meet the challenges of optimized stimulation of wells in massive carbonate reservoirs. Typically, the intervals to be produced in these reservoirs are very thick and highly heterogeneous. The permeability can range from a few milliDarcies to several Darcies. ExxonMobil and RasGas have jointly developed an integrated methodology to optimize matrix stimulation of the Khuff reservoir, a large, complex carbonate reservoir in the North Field of Qatar. The integrated methodology is a continuous process which consists of five main elements: reservoir objectives, completion strategy, stimulation design, implementation, and evaluation. The process was introduced by ExxonMobil in an earlier paper, which focused on the general laboratory testing and process modeling.1 This paper discusses how the integrated carbonate stimulation methodology was customized and implemented by RasGas and ExxonMobil as a critical component of the North Field development, focusing on the stimulation strategy, design, and results obtained. The carbonate stimulation design methodology cycle, specifically as applied to the North Field, is shown in Figure 1. The reservoir objectives for the development of large fields often span multiple heterogeneous producing horizons containing many layers with varying rock properties. From a resource standpoint, the ultimate objective is to economically extract the maximum amount of hydrocarbon from the reservoir. In order to accomplish this, the optimum production flow profile for reservoir depletion is required.