A New Method for History Matching and Forecasting Shale Gas/Oil Reservoir Production Performance with Dual and Triple Porosity Models

Different methods have been proposed for history matching production of shale gas/oil wells which are drilled horizontally and usually hydraulically fractured with multiple stages. These methods are simulation, analytical models, and empirical equations. It has been well known that among the methods listed above, analytical models are more favorable in application to field data for two reasons. First, analytical solutions are faster than simulation, and second, they are more rigorous than empirical equations. Production behavior of horizontally drilled shale gas/oil wells has never been completely matched with the models which are described in this thesis. For shale gas wells, correction due to adsorption is explained with derived equations. The algorithm which is used for history matching and forecasting is explained in detail with a computer program as an implementation of it that is written in Excel's VBA. As an objective of this research, robust method is presented with a computer program which is applied to field data. The method presented in this thesis is applied to analyze the production performance of gas wells from Barnett, Woodford, and Fayetteville shales. It is shown that the method works well to understand reservoir description and predict future performance of shale gas wells. Moreover, synthetic shale oil well also was used to validate application of the method to oil wells. Given the huge unconventional resource potential and increasing energy demand in the world, the method described in this thesis will be the "game changing" technology to understand the reservoir properties and make future predictions in short period of time

Production Data Analysis in Unconventional Reservoirs with Rate-Normalized Pressure (RNP): Theory, Methodology, and Applications

Abstract Unconventional reservoirs, shale gas and oil for instance, have proven to be an important contributor to hydrocarbon production in North America. Horizontal wells with multiple transverse fractures unlocked these unconventional resources by attaining profitable production rates and increasing gas reserves for future years. A critical challenge in these types of reservoirs is characterizing the stimulated reservoir volume (SRV), by estimating the effective productive volume created during stimulation and quantifying the permeability of the formation. Recent approaches for rate and pressure data deconvolution have emphasized the benefits of using buildup responses acquired whenever the well is shut-in, often for operational reasons, to assess significant insights about heterogeneity and compartmentalization in conventional reservoirs. However, deconvolution performs poorly when the initial reservoir pressure is unknown and might generate ambiguous results when pressure data accuracy is questionable. Regular measurements of daily production rates and wellhead flowing pressures can provide important information about well completion, stimulation, and formation parameters. With effective data processing, rate-normalized pressure (RNP) converts variable-rate and variable-pressure data to an equivalent of the drawdown pressure response to constant-rate production. This reveals flow regimes that enable direct estimation of the formation permeability and the productive fracture extent in the SRV. Subsequently, observed field rates and pressures can be matched with a global model to refine the estimates from the flow regime analysis. Although numerical models can be used to match the data, in this study we employed an analytical flow regime equations that provides fast and accurate results that can be easily programmed. The proposed methodology was applied to production data from Barnett shale wells providing excellent results and demonstrating an efficient, fast, and cost effective method to estimate critical well and formation parameters in unconventional reservoirs. The same methodology can be used to diagnose wells from other unconventional resources.</jats:p

Completion Optimization of an Unconventional Shale Play: Implementation of a Successful Completion Design Optimization Plan and the Results

Abstract Success of any unconventional shale development depends heavily on the effectiveness of the completion design. Geology, lithology, and production mechanism are the key drivers that determine how prolific a shale play can be. Identification of the geological and reservoir characteristics of the shale play needs to be performed prior to optimizing the completion design. A comprehensive completion design optimization plan is then needed to effectively harness the resource-in-place. The plan needs to account for the variations in the geology, hydrocarbon types, yield, true vertical depths, etc. within the asset. An optimum completion design will be different for rocks with various geologic and reservoir properties. It is equally important to realize that different completion parameters have varying effect on the well performance and the well economics. It is a challenge for an asset team to develop an optimized completion plan by testing different completion parameters in different geological regions within an asset. Rigorous reservoir modeling and economic analysis are needed to determine the actual effect of a completion parameter on well performance. A change of a completion parameter may result in better well performance, but the net incremental cost associated with making that change might not be the best economic decision. This paper presents the workflow, the analysis, the results and implementation of the Eagle Ford shale completion design optimization plan. It also includes the details of the reservoir and economic analysis associated with each completion parameter test. Information presented in this paper will help completion engineers and asset teams design a workflow for selecting appropriate completion design solutions of an unconventional shale reservoir.</jats:p

A Semi-Analytic Method for History Matching Fractured Shale Gas Reservoirs

Abstract This paper presents a semi-analytic method to estimate reservoir parameters by history matching the production data of hydraulically fractured shale gas wells. The method is based on the analytical solutions to dual-porosity reservoir models. Algebraic equations developed by Bello and Wattenbarger (2010) for transient flow regimes which can occur in linear dual porosity model were used in this analysis. As far as practical values of reservoir parameters are involved, only two of the transient flow regimes would be seen in the field – bilinear and late linear. If matrix permeability is known, effective fracture permeability is estimated by doing regression on bilinear flow. Once bilinear flow is matched, linear flow part is also matched by regressing on fracture half length. Semi-analytic solutions are checked with actual data by making correction for gas properties change and desorption of gas at low pressures. When a satisfactory match of field data is obtained, reservoir parameters such as effective fracture and matrix permeability and OGIP can be estimated. Moreover, a future production of gas can be forecasted with estimated reservoir parameters for given economic constraints. The method was applied on hydraulically fractured shale gas wells from Barnett play. It gives good results in history matching and estimation of reservoir parameters. Considering the recent interests in development of unconventional reservoirs, this method is future promising technique in better understanding those types of reservoirs.</jats:p