Shale gas and/or oil play identification is subject to many screening processes for characteristics such as porosity, permeability, and brittleness. Evaluating shale gas and/or oil reservoirs and identifying potential sweet spots (portions of the reservoir rock that have high-quality kerogen content and brittle rock) requires taking into consideration multiple rock, reservoir, and geological parameters that govern production. The early determination of sweet spots for well site selection and fracturing in shale reservoirs is a challenge for many operators. With this limitation in mind, Optimization of Hydraulic Fracture Stages and Sequencing in Unconventional Formations develops an approach to improve the industry's ability to evaluate shale gas and oil plays and is structured to lead the reader from general shale oil and gas characteristics to detailed sweet-spot classifications. The approach uses a new candidate selection and evaluation algorithm and screening criteria based on key geomechanical, petrophysical, and geochemical parameters and indices to obtain results consistent with existing shale plays and gain insights on the best development strategies going forward. The work introduces new criteria that accurately guide the development process in unconventional reservoirs in addition to reducing uncertainty and cost.

Shale gas and/or oil play identification is subject to many screening processes for characteristics such as porosity, permeability, and brittleness. Evaluating shale gas and/or oil reservoirs and identifying potential sweet spots (portions of the reservoir rock that have high-quality kerogen content and brittle rock) requires taking into consideration multiple rock, reservoir, and geological parameters that govern production. The early determination of sweet spots for well site selection and fracturing in shale reservoirs is a challenge for many operators. With this limitation in mind, Optimization of Hydraulic Fracture Stages and Sequencing in Unconventional Formations develops an approach to improve the industry's ability to evaluate shale gas and oil plays and is structured to lead the reader from general shale oil and gas characteristics to detailed sweet-spot classifications. The approach uses a new candidate selection and evaluation algorithm and screening criteria based on key geomechanical, petrophysical, and geochemical parameters and indices to obtain results consistent with existing shale plays and gain insights on the best development strategies going forward. The work introduces new criteria that accurately guide the development process in unconventional reservoirs in addition to reducing uncertainty and cost.

PVT properties are necessary for reservoir/well performance forecast and optimization. In absence of PVT laboratory measurements, finding the right correlation to estimate accurate PVT properties could be challenging. PVT Property Correlations: Selection and Estimation discusses techniques to properly calculate PVT properties from limited information. This book covers how to prepare PVT properties for dry gases, wet gases, gas condensates, volatile oils, black oils, and low gas-oil ration oils. It also explains the use of artificial neural network models in generating PVT properties. It presents numerous examples to explain step-by-step procedures in using techniques designed to deliver the most accurate PVT properties from correlations. Complimentary to this book is PVT correlation calculator software. Many of the techniques discussed in this book are available with the software. This book shows the importance of PVT data, provides practical tools to calculate PVT properties, and helps engineers select PVT correlations so they can model, optimize, and forecast their assets.