Craig M. Freeman

Analysis of Mechanisms of Flow in Fractured Tight-Gas and Shale-Gas Reservoirs

In this paper we analyze by means of numerical simulation the mechanisms and processes of flow in two types of fractured tight gas reservoirs: shale and tight-sand systems. The numerical model includes Darcy’s law as the basic equation of multiphase flow and accurately describes the thermophysical properties of the reservoir fluids, but also incorporates other options that cover the spectrum of known physics that may be involved: non-Darcy flow, as described by a multi-phase extension of the Forschheimer equation that accounts for laminar, inertial and turbulent effects; stress-sensitive flow properties of the matrix and of the fractures, i.e., porosity, permeability, relative permeability and capillary pressure; gas slippage (Klinkenberg) effects; and, non-isothermal effects, accounting for the consequences of energy balance and temperature changes in the presence of phenomena such as Joule-Thompson cooling in the course of gas production. The flow and storage behavior of the fractured media (shale or tight sand) is represented by various options of the Multiple Interactive Continua (MINC) conceptual model, in addition to an Effective Continuum Method (ECM) option, and includes a gas sorption term that follows the Langmuir isotherm. Comparison to field data, analysis of the simulation results and parameter determination through history matching indicates that (a) the ECM model is incapable of describing the fractured system behavior, and (b) shale and tight-sand reservoirs exhibit different behavior that can be captured (albeit imperfectly) using some of the more complex options of the multi-continua fractured-system models. The sorption term is necessary to describe the behavior of shale gas reservoirs, and significant deviations from the field data are observed if it is omitted. Conversely, production data from tight-sand reservoirs can be adequately represented without accounting for gas sorption. All the other processes and mechanisms allow refinement of the match between predictions and observations, but appear to have secondorder effects in the description of flow through fractured tight gas reservoirs.

SeTES: A self-teaching expert system for the analysis, design, and prediction of gas production from unconventional gas resources

SeTES is a self-teaching expert system that (a) can incorporate evolving databases involving any type and amount of relevant data (geological, geophysical, geomechanical, stimulation, petrophysical, reservoir, production, etc.) originating from unconventional gas reservoirs, i.e., tight sands, shale or coalbeds, (b) can continuously update its built-in public database and refine the its underlying decision-making metrics and process, (c) can make recommendations about well stimulation, well location, orientation, design, and operation, (d) offers predictions of the performance of proposed wells (and quantitative estimates of the corresponding uncertainty), and (e) permits the analysis of data from installed wells for parameter estimation and continuous expansion of its database. Thus, SeTES integrates and processes information from multiple and diverse sources to make recommendations and support decision making at multiple time-scales, while expanding its internal database and explicitly addressing uncertainty. It receives and manages data in three forms: public data, that have been made available by various contributors, semi-public data, which conceal some identifying aspects but are available to compute important statistics, and a users private data, which can be protected and used for more targeted design and decision making. It is the first implementation of a novel architecture that allows previously independent analysis methods and tools to share data, integrate results, and intelligently and iteratively extract the most value from the dataset. SeTES also presents a new paradigm for communicating research and technology to the public and distributing scientific tools and methods. It is expected to result in a significant improvement in reserve estimates, and increases in production by increasing efficiency and reducing uncertainty.

Modeling and Performance Interpretation of Flowing Gas Composition Changes in Shale Gas Wells with Complex Fractures

Limited attempts have been made to model shale gas reservoirs on a compositional basis. Multiple distinct physical phenomena influence the behavior of reservoir fluids in shale, resulting in measurable compositional changes in the produced gas over time. These phenomena include differential desorption, fractionation via phase change, and preferential diffusion. To address these phenomena, we have developed a compositional numerical model which describes the coupled processes of diffusion and desorption. We have also developed a tool for generating simulation grids capturing fracture geometries of realistic complexity. By combining the physics of flow in complex fractures with diffusion through nanopores, we show how gas composition changes during production. We identify and illustrate signature trends in the flowing gas composition according to our model. In addition, we present a workflow for the integration of measured gas composition data into traditional production data analysis. We prove that the onset of various transient flow regimes that are unique to shale gas reservoir systems can be identified in the model-based flowing composition data. For example, the transition from fracture-drainage to matrix-drainage can be identified by a characteristic trend in flowing gas composition. Some reservoir properties can be determined through analysis of the compositional shift in the flowing gas. This work expands the current understanding of well performance for shale gas to include physical phenomena that lead to compositional changes for realistic fracture configurations. This work can be used to optimize fracture and completion design, improve well performance analysis and provide more accurate reserves estimation. In this work we develop a numerical model which captures multicomponent desorption, diffusion, and phase behavior in ultra-tight rocks, we present a grid generation technique which captures the complexity of shale system fractures, and we validation of our interpretations of diagnostic trends.

Evaluation of Well Performance for the Slot-Drill Completion in Low- and Ultralow-Permeability Oil and Gas Reservoirs

Lowto ultralow-permeability formations require “special” treatments/stimulation to make them produce economical quantities of hydrocarbon, and at the moment, multistage hydraulic fracturing (MSHF) is the most commonly used stimulation method for enhancing the exploitation of these reservoirs. Recently, the slotdrill (SD) completion technique was proposed as an alternative treatment method in such formations (Carter 2009). This paper documents the results of a comprehensive numerical-simulation study conducted to evaluate the production performance of the SD technique and compare its performance to that of the standard MSHF approach. We investigated three lowpermeability formations of interest—namely, a shale-gas formation, a tight-gas formation, and a tight/shale-oil formation. The simulation domains were discretized with Voronoi-gridding schemes to create representative meshes of the different reservoir and completion systems modeled in this study. The results from this study indicated that the SD method does not, in general, appear to be competitive in terms of reservoir performance and recovery compared with the more traditional MSHF method. Our findings indicate that the larger surface area to flow that results from the application of MSHF is much more significant than the higher conductivity achieved by use of the SD technique. However, there may exist cases, for example, a lack of adequate water volumes for hydraulic fracturing, or very high irreducible water saturation that leads to adverse relative permeability conditions and production performance, in which the lowcost SD method may make production feasible from an otherwise challenging (if not inaccessible) resource.