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Pei, Yanli (The University of Texas at Austin) | Yu, Wei (The University of Texas at Austin / Sim Tech LLC) | Sepehrnoori, Kamy (The University of Texas at Austin) | Gong, Yiwen (Sim Tech LLC / The Ohio State University) | Xie, Hongbin (Sim Tech LLC) | Wu, Kan (Texas A&M University)
The extensive depletion of the development target has triggered the demand for infill drilling in the upside target of multilayer unconventional reservoirs. To optimize the hydraulic fracturing design of newly drilled wells, we need to investigate the stress changes in the upside target induced by parent-well production. In this work, an integrated parent-child workflow is presented to model the spatial-temporal stress evolution and propose the optimal development strategy for the upside target using a data set from the Permian Basin. The stress dependence of matrix permeability and fracture conductivity is determined based on available experimental data and incorporated in our reservoir simulation with the aid of an embedded discrete fracture model (EDFM). With calibrated reservoir properties from history matching of an actual well in the development target (i.e., 3rd BS Sand), we run the finite element method (FEM) based geomechanics simulator to predict the 3D spatial-temporal evolution of the local principal stresses. A displacement discontinuity method (DDM) hydraulic fracture model is then applied to simulate the multi-cluster fracture propagation in the upside target (i.e., L2BSSh) with the updated heterogeneous stress field. Numerical results indicate that stress field redistribution associated with parent-well production not only occurs within the development target but also vertically propagates to the upside target. A smaller parent-child horizontal offset induces a severer deviation of child-fractures towards the parent wellbore, resulting in more substantial well interference and less desirable oil and gas production. The parent-child fracture overlapping ratio in our study is in 0.6 ~ 0.8 for the 400 ft horizontal offset and 0.2 ~ 0.5 for the 600 ft horizontal offset. Varying the parent-child vertical offset gives the same trend as we change the horizontal offset. But with a delayed infill time, placing child-well in different layers causes more significant variation in the ultimate recovery. Moreover, infill operations at an earlier time are less affected by parent-well depletion because of the more homogeneous stress state. The candidate locations to implement infill-wells are suggested in the end for different infill timing by co-simulation of the parent-child production. With the reservoir-geomechanics-fracture model, this work provides a general workflow to optimize the child-well completion in multilayer unconventional reservoirs. The conclusions drawn from this study are of guiding significance to the subsequent development in the Permian Basin.
Given the state of the oil & gas industry today, i.e., low hydrocarbon prices and a global health crisis still in high gear, making good business decisions is more crucial than ever. Deciding which wells to keep open for production, which wells to shut-in, which wells to re-stimulate for immediate production, and which new wells to drill, if any, may directly impact a business' financial survival. This is true for both conventional and unconventional assets, but of significantly more concern to the unconventional asset investor, because incremental production is already capital-intensive at the best of times. Over the last decade, unconventional resources have become a significant source of the total production output in various parts of the world, and the primary stimulation treatment used is hydraulic fracturing. This technique sections a wellbore into multiple stages into which highly pressurized fluid is pumped at various fracture initiation locations. Historically, the number of stages and the number of clusters per stage, has primarily been based on total lateral length, previous experience in the same or similar fields, and on investment considerations, with a strong tendency towards decreasing stage and fracture spacing (i.e., increasing stage and fracture count). Field experience showing non-productive and full-physics simulations suggest room for improvement and indicate that there must be an optimal stimulation treatment that maximizes profit. Beyond this point, adding another stage in the treatment becomes more expensive than what can be recuperated by incrementally increased production. Thus, in the current work, the problem is posed as a classic constrained optimization problem and solved using Monte Carlo methods. Results show that in general, profitability of the production revenue is very sensitive to the reservoir recovery factor, porosity, drainage volume for the lease window, and, ultimately, the market price. Introduction Unconventional wells are challenging in many ways, and significant capital investment combined with relatively short production periods makes exploitation of these types of reservoirs a balancing act between costs and profit. Wells can run in the millions when drilling and completion costs are accounted for, with completion costs accounting for more than half of the capital requirement (EIA 2016). Fortunately, the completion details are one of the few inputs that can be adjusted in the field, which allows for fine-tuning to local conditions. In this work, we employ hydraulic fracturing as the stimulation technique, and note that it is the most common type of completion technique currently in use. During hydraulic fracturing, fluid is injected into a wellbore at high pressure to create cracks in the sub-surface in the neighborhood of the wellbore, through which natural gas and oil flow more freely than through the low-permeability formations typical of unconventional reservoirs. The pressurized fluid typically carries propping material such as sand, which is intended to hold open fractures after fracturing pressure is relieved and shut-in begins. The origins of hydraulic fracturing date back to early experiments in the 1940s at the Hugoton gas field in Grant County of southwestern Kansas by Stanolind (Charlez 1997; Montgomery et al. 2010), and one of the first commercially successful applications of the new technology in the 1950s. As of 2012, about 2.5 million "frac jobs" had been performed worldwide on oil and gas wells; over one million of those within the U.S. (King 2012). In years past, such stimulation treatment was generally necessary to achieve profitable flow rates in shale gas, tight gas, tight oil, and coal seam gas wells (Charlez 1997), but in today's market environment, using the optimal stimulation treatment is all but economic requirement for economic survival.
Abstract A workflow is presented which places far greater emphasis on formation lithology than is usually employed during pore pressure and geomechanical studies. Advanced classification techniques are linked with conventional pore pressure prediction and geomechanical modelling methods to implement the new workflow. The lithological classifications which are developed permit more robust predictions by facilitating the constraint of pore pressure and geomechanical results to available well data. Lithological assignments are developed from well logs using a Bayesian-based multivariate clustering analysis technique which yields a probabilistic Electroclass at each depth along the wellbore. The probabilistic results are analysed with an Expert System that automatically assigns a Lithology to the Electroclass at each depth. The Expert System can be modified for different regions and adjusted (and overruled) by an experienced analyst. The resulting multivariate model, with probabilistic lithological assignment, is used to QC, and if necessary predict, well log curves in missing intervals along the wellbore. Thus, interval velocities across the complete well profile from surface to total depth can be established from well log sonic data. These lithology-dependent velocities are then used to develop pore pressure predictions using an effective stress method in which the governing parameters are themselves lithologically dependent. Likewise, geomechanical properties such as Poisson's Ratio, Young's Modulus, Brittleness Index, and the minimum horizontal stress are calculated using Lithology-dependent parameters. An example is presented for an onshore US unconventional formation in which multiple wells are used to develop a robust lithological classification. The developed lithology then controls the wireline log curve predictions and ultimately the pore pressure and geomechanical predictions in selected wells. The impact of different lithologies on pore pressure and geomechanical estimates can be clearly seen and the impact of parameter setting ascertained for each. It is concluded that predictions of pore pressure and geomechanical properties are considerably enhanced by the far better understanding and consistent inclusion of lithology.
Abstract Frac fluid delivery is selective in effect, so must fracture models. Here, a physics-based analytical model, called nine-grain model, is presented for production forecasting in multifrac horizontal wells in unconventional reservoirs, where the utilized formulation inherently enables defining three-dimensional non-uniform SRVs, selective frac-hits, and pressure- and time-dependent permeabilities. The model is validated by constructing case studies of liquid and gas reservoirs and comparing the results with numerical simulations. In cases with both production history and fracing-induced microseismic data available, the SRV's spatial structure is extracted using a hybrid four-level straight-line technique that links volumetric RTA estimations to morphometric microseismic analysis and entails plots of plasticity, diffusivity, flowing material balance and early linear flow. By applying our model to an oil well in Permian Basin, we demonstrate that the knowledge gained from the coupled microseismic-RTA contributes to resolving the non-uniqueness of RTA solutions. The proposed reservoir modeling procedure enables efficient incorporation of microseismic interpretations in modern RTA while honoring the SRV space-time variability, thus facilitates informed decision making in spacing design of wells and perforation clusters. Introduction Frac-hits. A frac-hit can be defined as observing a perturbation in the well production rate and/or pressure that is induced by a child offset (or an infill) well, usually triggered by pressure sinks created around parent wells or high permeability lithofacies. A frac-hit that temporarily alters the parent well productivity is called a communication frac-hit, and those with long-term effects, generally caused by fracture interference, are referred as interference frac-hits. A frac-hit may also compromise the productivity of the child well itself since the existing pressure sinks distribute the fracing energy in a larger area and might lead to an asymmetric fracture growth around the child well. Besides the parent well operational condition, the microseismic monitoring of fracing can potentially indicate interference frac-hits as it reveals fracture overlaps and any preferential fracture dilation towards existing wells. Depending on the rock and fluid properties, well age, parent-child horizontal and vertical distances, and the spatial extent of Stimulated Reservoir Volume (SRV), the constructive (Esquivel and Blasingame 2017) or destructive (King et al. 2017, Ajani and Kelkar 2012) effects of frac-hits can be experienced by fractures, SRV or the entire drainage volume (stimulated and non-stimulated zones), usually by impacting rock multiphase fluid interfacial arrangements and/or changing dimensions of conductive fractures. Aside from prevention, thoroughly reviewed by Whitfield et al. (2018), it is essential to incorporate frac-hits into production forecasting models, which to date, is not yet as straightforward as their detection. Both types of frac-hits cause a change in the well productivity over time which is not necessarily correlated with pressure, and hence, complicate the reservoir modeling process.
Abstract Hydraulic fracturing (HF) is a very complex engineering process. It involves rock and fluid mechanics, mixed mode rock failure and transportation of individual proppant particles. This process is multiscale both in time and spatial domains that is why it is almost impossible to create a fully coupled 3D model with a detailed description of physical and chemical processes even with significant assumptions. Recent data indicates well completion becomes more expensive than the drilling itself for several unconventional reservoirs. The reason is an increase of fluid and proppant pumped at high rates. Thus, the critical importance of engineering optimization of fracture spacing and individual pumping schedule for maximization of Net Present Value (NPV), Estimated Ultimate Recovery (EUR), and other metrics in the "lower for longer" price environment. Unfortunately, unconventional operators see little value in fracture modeling because of its complexity and amount of data required for any reasonable predictive power. That is why many companies consider geometric design as the cheapest and hence the most efficient option thus resulting in trial and error to optimize HF design. In this paper we use publicly available well logs and completion data covering the Midland Basin from the University Lands website. We also demonstrate that HF model calibration with microseismic data and stochastically generated Discrete Fracture Network (DFN), although is a challenging task, may improve our understanding of fracture design pitfalls and to become an essential step for optimum engineering design. Insights from our work can be useful to increase the predictive power of in-house models and reduce total cost and effort involved in this complex modeling.
Abstract While marine organic-rich mudstones (aka black shales) have been effectively described in recent years, developing depositional models has lagged. Without depositional models, predictability of facies and properties remains a major problem. Sequence stratigraphy provides an answer. Sea level change controls sedimentation and circulation. Failure of masking sedimentation determines where marine black shales are expressed, and explains why they preferentially occur in carbonates and in the Paleozoic. In basinal organic-rich mudstones, which lack subaerial exposure surfaces, sequences can be identified by recognition of systematic variation in the rate of deposition. Episodicity and nondeposition are important considerations; and several different environments may be expressed within a black shale. But methods beyond simple observation of "unconformities" are necessary. Several parameters directly reflect rate of deposition, and together can be a powerful indicator of the depositional framework. Each comes from a different aspect of reduced sedimentation. The abundance of phosphatic fossil debris is a function of dilution by sedimentation. Illite crystallininty is a function of the length of time it is exposed to bottom water, regardless of oxidizing conditions. The relative abundances of organic matter type is a function of the length of time exposed to oxidizing conditions and the reciprocal rate of burial in reducing conditions. Other lines of evidence may also contribute to the model. While individually they may be ambiguous, the ability to correlate different signals from different processes reinforces the interpretation. The depositional model is testable against sequence models and against sequences recognized on adjacent shelves, constraining the intensity and frequency patterns of the sequences identified in the basin. A sequence-based depositional model can help to identify lateral and vertical changes in rock properties within the basinal shales, particularly as they apply to distribution of organic matter type and content (which determine "sweet spots"), porosity, cements and bedding properties. Both actualistic and probabilistic models may be developed and may be helpful with risk analysis. While detailed analysis of every well is impractical, the application of models derived from key sections can greatly enhance predictability.