A multidisciplinary approach integrates fracture characteristics, reservoir production, and stress-field evolution to design and optimize the development of unconventional assets. In this approach, fracture modeling and advanced rate-transient techniques are used to constrain fracture geometry and depletion characteristics of existing wells. This knowledge is used in finite-element geomechanical modeling to predict fracture orientation in nearby wells. In this paper, an integrated methodology is described and applied to a shale-gas pad as a case study.
Introduction
Although it is generally accepted that geomechanical stresses are important for understanding fracture propagation in shales with low contrast in principal compressive stresses, the absence of precise knowledge of input parameters needed for reliable predictions has limited the broad use and applicability of geomechanical models. Parameters such as permeability, fracture half-length, number of propagated fractures, and geological heterogeneity still carry much uncertainty for shales and can have a significant effect on model predictions. A methodology is presented to address some of these limitations by integrating knowledge derived from production and fracturing data to reduce the uncertainty in key parameters and enable realistic predictions (Fig. 1).
The spatial and temporal evolution of stresses for multiple horizontal fractured shale-gas wells on a pad has been investigated by explicitly modeling each of the hydraulic fractures extending from the wellbore. The models are constructed by use of simplifying assumptions of planar biwing fractures. Both 2D plane-strain and full 3D formulations are used. The results reveal significant reorientation of principal stresses thousands of feet away from a producing well in addition to the anticipated near-fracture stress changes. The reorientation of stresses far from a producing well can have a significant effect on hydraulic-fracture propagation during stimulation of new infill or neighboring wells.
Methodology
A multidisciplinary approach integrating aspects related to completion, reservoir production, and geomechanics was used to optimize development of unconventional gas assets.
A detailed workflow showing the interaction among all three disciplines is highlighted in Fig. 2. The main inputs for this process are reservoir, geological, and mechanical properties of the formation, which are used in hydraulic-fracture modeling and analysis, production-data analysis (diagnostic plots), flowing material balance, numerical history matching, and finite-element geomechanics analysis. The production analysis determines the dominant flow regimes in the well to infer fracture-to-fracture and well-to-well interference. Using information from production-data analysis and fracture height, estimated ultimate recovery (EUR) and drainage area are calculated from type curves and numerical simulations. Finite-element analysis (FEA) is conducted to determine evolution of stresses from production, shut-in, injection, and offset-well completion. These geomechanical models use reservoir properties, number of fractures per stage, drainage widths, and reservoir pressures to predict the stresses surrounding single or multiple wells.
Case Study
The shale-gas pad used for the case study consists of two primary wells (drilled and fractured at different times) and four infill wells that had been drilled but not fractured. The objectives of the case study were twofold: (1) to assess the potential for interference between the primary (Wells 1 and 2) and infill (Wells 3 through 6) wells from fracturing of the infill wells and (2) to identify a completion strategy to minimize interference.
Two key observations were made by closely inspecting the production data from Wells 1 and 2. First, significantly different productivity between Wells 1 and 2 was observed, despite the two wells being close to each other. Normalizing the initial production by lateral length showed that Well 1 had twice the productivity of Well 2, despite more sand being pumped into the latter. Second, well-to-well connectivity induced by nearby fracturing operations was observed. Several spikes in the production rates of Well 1 were observed. Most of these spikes in gas rate were associated with a fracturing event taking place close to the pad. These observations suggest well-to-well connectivity during a fracturing operation when the reservoir is dilated with millions of gallons of fracturing fluid.
Fracture Modeling
The authors first sought to take advantage of the available fracture-treatment and pumping-pressure data to constrain fracture length and height and the number of fractures per stage. Fracture modeling was also conducted to estimate fracture height. Mechanical properties (Young’s modulus, Poisson’s ratio, fracture toughness, and critical stress) of shales were derived from sonic logs and correlations using conventional analysis. Mechanical properties along with wellbore and treatment designs were added to a fracture simulator to estimate fracture heights and lengths.
Reservoir Modeling
To constrain the reservoir and fracture characteristics further, a Wattenbarger diagnostic plot based on advanced rate-transient analysis was used. First, the diagnostic Wattenbarger plot was made to identify the dominant flow regimes experienced by Well 1. A half-slope signature was observed for an initial linear or transient flow (also confirmed by a square-root-of-time plot) followed by a slope of unity, indicating possible boundary effects. The observation of boundary effects was interpreted as interference between fractures on the same horizontal lateral. These observations suggested that, although the transient linear flow was anticipated to last for a dominant part of a well’s life because of ultralow permeabilities, production data suggested an early transition to a boundary-dominated flow depending on fracture character. Next, a flowing material balance was performed to estimate the stimulated rock volume, assuming minimum contribution of gas from the unstimulated rock. This stimulated rock volume, along with the estimate of fracture height from the fracture model, provided an estimate for the drainage area of Well 1 of 130 acres. It is important to note that the method used to calculate this drainage area did not involve making any assumptions about the permeability, a parameter that has a high degree of uncertainty.
On the basis of production, reservoir properties, and fracture height and including uncertainties, the drainage area of Well 1 was estimated to be between 65 and 130 acres. On the basis of this result, the already-drilled infill wells have a very high likelihood of lying within the drainage area of Well 1, making it very likely that these wells would communicate during fracturing operations.
To obtain an estimate for permeability, history matching of the production data was performed using a numerical model with fine gridding to capture sharp pressure gradients near the fractures. The history matching assumed biwing fractures uniformly spaced over the lateral length. Because of occasional spikes in the gas rate (resulting from fracturing in neighboring wells), a perfect history match could not be obtained at those times. To reduce this non-uniqueness, the derivative of the integral of normalized pressure of the history-matched data was plotted to identify the flow regimes uniquely. This additional constraint significantly reduced the nonuniqueness, and the best history match yielded a permeability of 400 nd and an average of 2.4 fractures per stage, totaling 12 fractures for five stages.
Geomechanical Modeling
On the basis of the fracture and reservoir analyses, interference was anticipated between primary and infill wells during fracturing of the infill wells. To gauge the magnitude of this interference and develop effective strategies to minimize well interference, geomechanical models were run by use of a commercial finite-element code to predict the propagation of fractures in the infill wells and to evaluate strategies (based on injection, shut-in, and production in primary or infill wells) to steer the propagation of fractures in the infill wells (Wells 3 and 6) away from the highly productive primary wells.
A geomechanical finite-element model was created for the pad. In the model, the evolution of stresses resulting from production in Well 1 until Well 2 was fractured was simulated. Soon after production initiation in Well 1, the high pore-pressure gradients are confined near the fractures (consistent with the early-time linear flow exhibited by Well 1), and the stress orientation has not shifted appreciably from the initial state. To predict the evolution of stresses after Well 2 was fractured, a new mesh was generated to include Well 2 in the model.
In summary, geomechanical simulations predict stresses that suggest propagation of tilted fractures in Well 2 and longitudinal fractures for Wells 4 and 5, fracture geometries that are otherwise not obvious. Potential reasons for the lower performance of Well 2 compared with Well 1 despite their proximity are (1) the difference in the fracture character (transverse vs. tilted fractures) as predicted by the models and (2) the large skin damage observed for Well 2 compared with Well 1.
A 3D finite-element model of a single well was developed to verify the assumption of 2D plane strain in the FEA models used in the integrated-modeling approach. Although the drainage area is similar to the fractured area, both the 2D and 3D models show that the stress field is altered well beyond the fractured region.
Conclusions
Overall, this case study demonstrated that the integrated workflow that incorporates fracture, reservoir, and geomechanical models can be used to develop customized plans for drilling and completion of infill wells for a given pad. The strength of the integrated methodology used to derive these results lies in the use of all of the available data and reasonably constraining the model parameters. The product of this approach is obtaining more-reliable and customized predictions for every well or pad rather than using generalized numbers for parameters such as well spacing. By understanding the effect of stress-field alterations on fracture-propagation patterns, early decisions on infill-well placement, orientation, and timing can be made to minimize early well-to-well interference and damage caused by fracturing of neighboring wells.
This article, written by Editorial Manager Adam Wilson, contains highlights of paper SPE 164018, “Integration of Fracture, Reservoir, and Geomechanics Modeling for Shale Gas Reservoir Development,” by Jugal K. Gupta, SPE, Richard A. Albert, SPE, Matias G. Zielonka, SPE, Yao Yao, SPE, Elizabeth Templeton-Barrett, SPE, Shalawn K. Jackson, SPE, and Wadood El-Rabaa, SPE, ExxonMobil Upstream Research Company, and Heather A. Burnham, SPE, and Nancy H. Choi, SPE, XTO Energy, prepared for the 2013 SPE Middle East Unconventional Gas Conference and Exhibition, Muscat, Oman, 28–30 January. The paper has not been peer reviewed.