Reservoir characterization as a discipline grew out of the recognition that more oil and gas could be extracted from reservoirs if the geology of the reservoir was understood. Prior to that awakening, reservoir development and production were the realm of the petroleum engineer. In fact, geologists of that time would have felt slighted if asked by corporate management to move from an exciting exploration assignment to a more mundane assignment working with an engineer to improve a reservoir's performance. Slowly, reservoir characterization came into its own as a quantitative, multidisciplinary endeavor requiring a vast array of skills and knowledge sets. Perhaps the biggest attractor to becoming a reservoir geologist was the advent of fast computing, followed by visualization programs and theaters, all of which allow young geoscientists to practice their computing skills in a highly technical work environment. Also, the discipline grew in parallel with the evolution of data integration and the advent of asset teams in the petroleum industry. Finally, reservoir characterization flourished with the quantum improvements that have occurred in geophysical acquisition and processing techniques and that allow geophysicists to image internal reservoir complexities. - Practical resource describing different types of sandstone and shale reservoirs - Case histories of reservoir studies for easy comparison - Applications of standard, new, and emerging technologies

Carbonate reservoirs contain an increasingly important percentage of the worlds hydrocarbon reserves. This volume presents key recent advances in carbonate exploration and reservoir analysis.

In this chapter, the principles of reservoir modeling, workflows and their applications have been summarized. Reservoir modeling is a multi-disciplinary process that requires cooperation from geologists, geophysicists, reservoir engineers, petrophysics and financial individuals, working in a team setting. The best model is one that provides quantitative properties of the reservoir, though this is often difficult to achieve. There are three broad steps in the modeling process. The team needs to first evaluate the data quality, plan the proper modeling workflow, and understand the range of uncertainties of the reservoir. The second step is data preparation and interpretation, which can be a long, tedious, but essential process, which may include multiple iterations of quality control, interpretation, calibration and tests. The third step is determining whether to build a deterministic (single, data-based model) or stochastic (multiple geostatistical iterations) model. The modeling approach may be decided by the quality and quantity of the data. There is no single rule of thumb because no two reservoirs are identical. Object-based stochastic modeling is the most widely used modeling method today. The modeling results need to be constrained and refined by both geologic and mathematical validation. Variogram analysis is very important in quality control of object-based stochastic modeling. Outcrops are excellent sources of continuous data which can be incorporated into subsurface reservoir modeling either by 1) building an outcrop “reservoir” model, or 2) identifying and developing outcrop analogs of subsurface reservoirs. Significant upscaling of a reservoir model for flow simulation may well result in an erroneous history match because the upscaling process often deletes lateral and vertical heterogeneities which may control or affect reservoir performance, particularly in a deterministic model. Reservoir uncertainties are easier to manipulate by object-based stochastic models. Choosing the best realization approach for the reservoir model is the key to predicting reservoir performance in the management of reservoirs.

Over the past 20 years there has been a major growth in efforts to quantify the geometry and dimensions of sediment bodies from analogues to provide quantitative input to geological models. The aim of this volume is to examine the current state of the art, from both an industry and an academic perspective. Contributions discuss the challenges of extracting relevant data from different types of sedimentary analogue (outcrop, process models, seismic) and the application and significance of such information for improving predictions from subsurface static and dynamic models. Special attention is given to modelling reservoir properties and gridding issues for predicting subsurface fluid flow. As such, the volume is expected to be of interest to both the geoscience community concerned with the fundamentals of sedimentary architecture as well as geological modellers and engineers interested in how these characteristics are modelled and influence subsurface predictions.

This book gives practical advice and ready to use tips on the design and construction of subsurface reservoir models. The design elements cover rock architecture, petrophysical property modelling, multi-scale data integration, upscaling and uncertainty analysis. Philip Ringrose and Mark Bentley share their experience, gained from over a hundred reservoir modelling studies in 25 countries covering clastic, carbonate and fractured reservoir types, and for a range of fluid systems – oil, gas and CO2, production and injection, and effects of different mobility ratios. The intimate relationship between geology and fluid flow is explored throughout, showing how the impact of fluid type, displacement mechanism and the subtleties of single- and multi-phase flow combine to influence reservoir model design. The second edition updates the existing sections and adds sections on the following topics: · A new chapter on modelling for CO2 storage · A new chapter on modelling workflows · An extended chapter on fractured reservoir modelling · An extended chapter on multi-scale modelling · An extended chapter on the quantification of uncertainty · A revised section on the future of modelling based on recently published papers by the authors The main audience for this book is the community of applied geoscientists and engineers involved in understanding fluid flow in the subsurface: whether for the extraction of oil or gas or the injection of CO2 or the subsurface storage of energy in general. We will always need to understand how fluids move in the subsurface and we will always require skills to model these quantitatively. The second edition of this reference book therefore aims to highlight the modelling skills developed for the current energy industry which will also be required for the energy transition of the future. The book is aimed at technical-professional practitioners in the energy industry and is also suitable for a range of Master’s level courses in reservoir characterisation, modelling and engineering. • Provides practical advice and guidelines for users of 3D reservoir modelling packages • Gives advice on reservoir model design for the growing world-wide activity in subsurface reservoir modelling • Covers rock modelling, property modelling, upscaling, fluid flow and uncertainty handling • Encompasses clastic, carbonate and fractured reservoirs • Applies to multi-fluid cases and applications: hydrocarbons and CO2, production and storage; rewritten for use in the Energy Transition.