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.

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.

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.

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.

Frequently a discrepancy is found between the stimulated shale volume (SSV) estimated from production data and the SSV expected from injected water and proppant volume. One possible explanation is the presence of a fracture network, often termed fracture complexity, that may have been opened or reopened during the hydraulic fracturing operation. The main objective of this work is to investigate the role of fracture complexity in resolving the apparent SSV discrepancy and to illustrate whether the presence of reopened natural fracture network can be observed in pressure and production data of shale gas wells producing from two shale formations with different well and reservoir properties. Homogeneous, dual porosity and triple porosity models are investigated. Sensitivity runs based on typical parameters of the Barnett and the Horn River shale are performed. Then the field data from the two shales are matched. Homogeneous models for the two shale formations indicate effective infinite conductivity fractures in the Barnett well and only moderate conductivity fractures in the Horn River shale. Dual porosity models can support effectively infinite conductivity fractures in both shale formations. Dual porosity models indicate that the behavior of the Barnett and Horn River shale formations are different. Even though both shales exhibit apparent bilinear flow behavior the flow behaviors during this trend are different. Evidence of this difference comes from comparing the storativity ratio observed in each case to the storativity ratio estimated from injected fluid volumes during hydraulic fracturing. In the Barnett shale case similar storativity ratios suggest fracture complexity can account for the dual porosity behavior. In the Horn River case, the model based storativity ratio is too large to represent only fluids from hydraulic fracturing and suggests presence of existing shale formation microfractures.

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The so-called "Arps" rate decline relations are by far the most widely used tool for assessing oil and gas reserves from rate performance. These relations (i.e., the exponential and hyperbolic decline relations) are empirical where the starting point for their derivation is given by the definitions of the "loss ratio" and the "derivative of the loss ratio", where the "loss ratio" is the ratio of rate data to derivative of rate data, and the "derivative of the loss ratio" is the "b-parameter" as defined by Arps [1945]. The primary goal of this work is the interpretation of the b-parameter continuously over time and thus the better understanding of its character. As is shown below we propose "monotonically decreasing functional forms" for the characterization of the b-parameter, in addition to the exponential and hyperbolic rate decline relations, where the b-parameter is assumed to be zero and constant, respectively. The proposed equations are as follow: b(t)=constant (Arps' hyperbolic rate-decline relation), []tbbtb10exp)(-bt= (exponential function), (power-law function), 10)(btbtb=)/(1)(10tbbtb+= (rational function). The corresponding rate decline relation for each case is obtained by solving the differential equation associated with the selected functional for the b-parameter. The next step of this procedure is to test and validate each of the rate decline relations by applying them to various numerical simulation cases (for gas), as well as for field data cases obtained from tight/shale gas reservoirs. Our results indicate that b-parameter is never constant but it changes continuously with time. The ultimate objective of this work is to establish each model as a potential analysis/diagnostic relation. Most of the proposed models yield more realistic estimations of gas reserves in comparison to the traditional Arps' rate decline relations (i.e., the hyperbolic decline) where the reserves estimates are inconsistent and over-estimated. As an example, the rational b-parameter model seems to be the most accurate model in terms of representing the character of rate data; and therefore, should yield more realistic reserves estimates. Illustrative examples are provided for better understanding of each b-parameter rate decline model. The proposed family of rate decline relations was based on the character of the b-parameter computed from the rate-time data and they can be applied to a wide range of data sets, as dictated by the character of rate data.