Shale gas formations are known to have low permeability. This low permeability can be as low as 100 nano darcies. Without stimulating wells drilled in the shale gas formations, it is hard to produce them at an economic rate. One of the stimulating approaches is by drilling horizontal wells and hydraulically fracturing the formation. Once the formation is fractured, different flow patterns will occur. The dominant flow regime observed in the shale gas formation is the linear flow or the transient drainage from the formation matrix toward the hydraulic fracture. This flow could extend up to years of production and it can be identified by half slop on the log-log plot of the gas rate against time. It could be utilized to evaluate the hydraulic fracture surface area and eventually evaluate the effectiveness of the completion job. Different models from the literature can be used to evaluate the completion job. One of the models used in this work assumes a rectangular reservoir with a slab shaped matrix between each two hydraulic fractures. From this model, there are at least five flow regions and the two regions discussed are the Region 2 in which bilinear flow occurs as a result of simultaneous drainage form the matrix and hydraulic fracture. The other is Region 4 which results from transient matrix drainage which could extend up to many years. The Barnett shale production data will be utilized throughout this work to show sample of the calculations. This first part of this work will evaluate the field data used in this study following a systematic procedure explained in Chapter III. This part reviews the historical production, reservoir and fluid data and well completion records available for the wells being analyzed. It will also check for data correlations from the data available and explain abnormal flow behaviors that might occur utilizing the field production data. It will explain why some wells might not fit into each model. This will be followed by a preliminary diagnosis, in which flow regimes will be identified, unclear data will be filtered, and interference and liquid loading data will be pointed. After completing the data evaluation, this work will evaluate and compare the different methods available in the literature in order to decide which method will best fit to analyze the production data from the Barnett shale. Formation properties and the original gas in place will be evaluated and compared for different methods.

This thesis presents the development of a semi-analytical technique that can be used to estimate the gas-in-place for volumetric gas reservoirs. This new methodology utilizes plotting functions, plots, extrapolations, etc. - where all analyses are based on the following governing identity. The 'governing identity' is derived and validated by others for pi less than 6000 psia. We have reproduced the derivation of this result and we provide validation using numberical simulation for cases where pi greater than 6000 psia. The relevance of this work is straightforward using a simple governing relation, we provide a series of plotting functions which can be used to extrapolate or interpret an estimate of gas-in-place using only production data (qg and Gp). The proposed methodology does not require a prior knowledge of formation and or fluid compressibility data, nor does it require average reservoir pressure. In fact, no formation or fluid properties are directly required for this analysis and interpretation approach. The new methodology is validated demonstrated using results from numerical simulation (i.e., cases where we know the exact answer), as well as for a number of field cases. Perhaps the most valuable component of this work is our development of a "spreadsheet" approach in which we perform multiple analyses interpretations simultaneously using MS Excel. This allows us to visualize all data plots simultaneously - and to "link" the analyses to a common set of parameters. While this "simultaneous" analysis approach may seem rudimentary (or even obvious), it provides the critical (and necessary) "visualization" that makes the technique functional. The base relation (given above) renders different behavior for different plotting functions, and we must have a "linkage" that forces all analyses to "connect" to one another. The proposed multiplot spreadsheet approach provides just such a connection.

Unconventional reservoir systems can best be described as petroleum (oil and/or gas) accumulations which are difficult to be characterized and produced by conventional technologies. In this work we present the development of a systematic procedure to evaluate well performance in unconventional (i.e., low to ultra-low permeability) reservoir systems. The specific tasks achieved in this work include the following: ● Integrated Diagnostics and Analysis of Production Data in Unconventional Reservoirs: We identify the challenges and common pitfalls of production analysis and provide guidelines for the analysis of production data. We provide a comprehensive workflow which consists of model-based production analysis (i.e., rate-transient or model matching approaches) complemented by traditional decline curve analysis to estimate reserves in unconventional reservoirs. In particular, we use analytical solutions (e.g., elliptical flow, horizontal well with multiple fractures solution, etc.) which are applicable to wells produced in unconventional reservoirs. ● Deconvolution: We propose to use deconvolution to identify the correlation between pressure and rate data. For our purposes we modify the B-spline deconvolution algorithm to obtain the constantpressure rate solution using cumulative production and bottomhole pressure data in real time domain. It is shown that constant-pressure rate and constant-rate pressure solutions obtained by deconvolution could identify the correlation between measured rate and pressure data when used in conjunction. ● Series of Rate-Time Relations: We develop three new main rate-time relations and five supplementary rate-time relations which utilize power-law, hyperbolic, stretched exponential, and exponential components to properly model the behavior of a given set of rate-time data. These relations are well-suited for the estimation of ultimate recovery as well as for extrapolating production into the future. While our proposed models can be used for any system, we provide application almost exclusively for wells completed in unconventional reservoirs as a means of providing estimates of time-dependent reserves. We attempt to correlate the rate-time relation model parameters versus model-based production analysis results. As example applications, we present a variety of field examples using production data acquired from tight gas, shale gas reservoir systems.

Inverse problems associated with reservoir characterization are typically underdetermined and often have difficulties associated with stability and convergence of the solution. A common approach to address this issue is through the introduction of prior constraints, regularization or reparameterization to reduce the number of estimated parameters. We propose a dual scale approach to production data integration that relies on a combination of coarse-scale and fine-scale inversions while preserving the essential features of the geologic model. To begin with, we sequentially coarsen the fine-scale geological model by grouping layers in such a way that the heterogeneity measure of an appropriately defined 'static' property is minimized within the layers and maximized between the layers. Our coarsening algorithm results in a non-uniform coarsening of the geologic model with minimal loss of heterogeneity and the ?optimal? number of layers is determined based on a bias-variance trade-off criterion. The coarse-scale model is then updated using production data via a generalized travel time inversion. The coarse-scale inversion proceeds much faster compared to a direct fine-scale inversion because of the significantly reduced parameter space. Furthermore, the iterative minimization is much more effective because at the larger scales there are fewer local minima and those tend to be farther apart. At the end of the coarse-scale inversion, a fine-scale inversion may be carried out, if needed. This constitutes the outer iteration in the overall algorithm. The fine-scale inversion is carried out only if the data misfit is deemed to be unsatisfactory. We propose a fast and robust approach to calibrating geologic models by transient pressure data using a trajectory-based approach that based on a high frequency asymptotic expansion of the diffusivity equation. The trajectory or ray-based methods are routinely used in seismic tomography. In this work, we investigate seismic rays and compare them with streamlines. We then examine the applicability of streamline-based methods for transient pressure data inversion. Specifically, the high frequency asymptotic approach allows us to analytically compute the sensitivity of the pressure responses with respect to reservoir properties such as porosity and permeability. It facilitates a very efficient methodology for the integration of pressure data into geologic models.

This dissertation presents several new techniques for the analysis of the long-term production performance of tight gas wells. The main objectives of this work are to determine pressure response function for long-term production for a the slightly compressible liquid case, to determine the original gas in place (OGIP) during pseudosteady state (PSS), to determine OGIP in the transient period, and to determine the effects of these parameters on linear flow in gas wells. Several methods are available in the industry to analyze the production performance of gas wells. One common method is superposition time. This method has the advantage of being able to analyze variable-rate and variable-pressure data, which is usually the nature of field data. However, this method has its shortcomings. In this work, simulation and field cases illustrate the shortcomings of superposition. I present a new normalized pseudotime plotting function for use in the superposition method to smooth field data and more accurately calculate OGIP. The use of this normalized pseudotime is particularly important in the analysis of highly depleted reservoirs with large change in total compressibility where the superposition errors are largest. The new tangent method presented here can calculate the OGIP with current reservoir properties for both constant rate and bottomhole flowing pressure (pwf) production. In this approach pressure-dependent permeability data can be integrated into a modified real gas pseudopressure,m(p), which linearizes the reservoir flow equations and provides correct values for permeability and skin factor. But if the customary real-gas pseudopressure, m(p) is used instead, erroneous values for permeability and skin factor will be calculated. This method uses an exponential equation form for permeability vs. pressure drop. Simulation and field examples confirm that the new correction factor for the rate dependent problem improves the linear model for both PSS and transient period, whether plotted on square-root of time or superposition plots.

Various analytical, semi-analytical, and empirical models have been proposed to characterize rate and pressure behavior as a function of time in tight/shale gas systems featuring a horizontal well with multiple hydraulic fractures. Despite a small number of analytical models and published numerical studies there is currently little consensus regarding the large-scale flow behavior over time in such systems. The purpose of this work is to construct a fit-for-purpose numerical simulator which will account for a variety of production features pertinent to these systems, and to use this model to study the effects of various parameters on flow behavior. Specific features examined in this work include hydraulically fractured horizontal wells, multiple porosity and permeability fields, desorption, and micro-scale flow effects. The theoretical basis of the model is described in Chapter I, along with a validation of the model. We employ the numerical simulator to examine various tight gas and shale gas systems and to illustrate and define the various flow regimes which progressively occur over time. We visualize the flow regimes using both specialized plots of rate and pressure functions, as well as high-resolution maps of pressure distributions. The results of this study are described in Chapter II. We use pressure maps to illustrate the initial linear flow into the hydraulic fractures in a tight gas system, transitioning to compound formation linear flow, and then into elliptical flow. We show that flow behavior is dominated by the fracture configuration due to the extremely low permeability of shale. We also explore the possible effect of microscale flow effects on gas effective permeability and subsequent gas species fractionation. We examine the interaction of sorptive diffusion and Knudsen diffusion. We show that microscale porous media can result in a compositional shift in produced gas concentration without the presence of adsorbed gas. The development and implementation of the micro-flow model is documented in Chapter III. This work expands our understanding of flow behavior in tight gas and shale gas systems, where such an understanding may ultimately be used to estimate reservoir properties and reserves in these types of reservoirs.

In practice today, pressure transient analysis (PTA) and production data analysis (PDA) are done separately and differently by different interpreters in different companies using different analysis techniques, different interpreter-dependent inputs, on pressure and production rate data from the same well, with different software packages. This has led to different analyses outputs and characterizations of the same reservoir. To avoid inconsistent results from different interpretations, this study presents a new way to integrate PTA and PDA on a single diagnostic plot to account for and see the early time and mid-time responses (from the transient tests) and late time (boundary affected/PSS) responses achievable with production analysis, on the same plot; thereby unifying short and long-term analyses and improving the reservoir characterization. The rate normalized pressure (RNP) technique was combined with conventional pressure buildup PTA technique. Data processing algorithms were formulated to improve plot presentation and a stepwise analysis procedure is presented to apply the new technique. The new technique is simple to use and the same conventional interpretation techniques as PTA apply. We have applied the technique to a simulated well case and two field cases. Finally, this new technique represents improvements over previous PDA methods and can help give a long term dynamic description of the well’s drainage area.

Various analytical, semi-analytical, and empirical models have been proposed to characterize rate and pressure behavior as a function of time in tight/shale gas systems featuring a horizontal well with multiple hydraulic fractures. Despite a small number of analytical models and published numerical studies there is currently little consensus regarding the large-scale flow behavior over time in such systems. The purpose of this work is to construct a fit-for-purpose numerical simulator which will account for a variety of production features pertinent to these systems, and to use this model to study the effects of various parameters on flow behavior. Specific features examined in this work include hydraulically fractured horizontal wells, multiple porosity and permeability fields, desorption, and micro-scale flow effects. The theoretical basis of the model is described in Chapter I, along with a validation of the model. We employ the numerical simulator to examine various tight gas and shale gas systems and to illustrate and define the various flow regimes which progressively occur over time. We visualize the flow regimes using both specialized plots of rate and pressure functions, as well as high-resolution maps of pressure distributions. The results of this study are described in Chapter II. We use pressure maps to illustrate the initial linear flow into the hydraulic fractures in a tight gas system, transitioning to compound formation linear flow, and then into elliptical flow. We show that flow behavior is dominated by the fracture configuration due to the extremely low permeability of shale. We also explore the possible effect of microscale flow effects on gas effective permeability and subsequent gas species fractionation. We examine the interaction of sorptive diffusion and Knudsen diffusion. We show that microscale porous media can result in a compositional shift in produced gas concentration without the presence of adsorbed gas. The development and implementation of the micro-flow model is documented in Chapter III. This work expands our understanding of flow behavior in tight gas and shale gas systems, where such an understanding may ultimately be used to estimate reservoir properties and reserves in these types of reservoirs.

Production data are the most abundant data in the field. However, they can often be of poor quality because of undocumented operational problems, or changes in operating conditions, or even recording mistakes (Nobakht et al. 2009). If this poor quality or inconsistency is not recognized as such, it can be misinterpreted as a reservoir issue other than the data quality problem that it is. Thus quality control of production data is a crucial and necessary step that must precede any further interpretation using the production data. To restore production data, we propose to use the capacitance resistance model (CRM) to realize data reconciliation. CRM is a simple reservoir simulation model that characterizes the connectivity between injectors and producers using only production and injection rate data. Because the CRM model is based on the continuity equation, it can be used to analyze the production corresponding to the injection signal in the reservoir. The problematic production data are then put into the CRM model directly and the resulting CRM output parameters are used to evaluate what the correct production response would be under current injection scheme. We also make sensitivity analysis based on synthetic fields, which are heterogeneous ideal reservoir models with imposed geology and well features in Eclipse. The aim is to show how bad data could be misleading and the best way to restore the production data. Using the CRM model itself to control data quality is a novel method to obtain clean production data. We can then apply the new clean production data in reservoir simulators or any other processes where production data quality matters. This data quality control process can help better understand the reservoir, analyze its behavior in a more ensured way and make more reliable decisions. / text

There have been many attempts to use mathematical method in order to characterize shale gas/oil reservoirs with multi-transverse hydraulic fractures horizontal well. Many authors have tried to come up with a suitable and practical mathematical model. To analyze the production data of a shale reservoir correctly, an understanding and choosing the proper mathematical model is required. Therefore, three models (the homogeneous linear flow model, the transient linear dual porosity model, and the fully transient linear triple porosity model) will be studied and compared to provide correct interpretation guidelines for these models. The analytical solutions and interpretation guidelines are developed in this work to interpret the production data of shale reservoirs effectively. Verification and derivation of asymptotic and associated equations from the Laplace space for dual porosity and triple porosity models are performed in order to generate analysis equations. Theories and practical applications of the three models (the homogeneous linear flow model, the dual porosity model, and the triple porosity model) are presented. A simplified triple porosity model with practical analytical solutions is proposed in order to reduce its complexity. This research provides the interpretation guidelines with various analysis equations for different flow periods or different physical properties. From theoretical and field examples of interpretation, the possible errors are presented. Finally, the three models are compared in a production analysis with the assumption of infinite conductivity of hydraulic fractures.