This comprehensive book highlights soft computing and geostatistics applications in hydrocarbon exploration and production, combining practical and theoretical aspects. The book spans a wide spectrum of applications in the oil industry, crossing many discipline boundaries such as geophysics, geology, petrophysics and reservoir engineering.

It is complemented by several tutorial chapters on fuzzy logic, neural networks and genetic algorithms and geostatistics to introduce these concepts to the uninitiated. The application areas include prediction of reservoir properties (porosity, sand thickness, lithology, fluid), seismic processing, seismic and bio stratigraphy, time lapse seismic and core analysis.
There is a good balance between introducing soft computing and geostatistics methodologies that are not routinely used in the petroleum industry and various applications areas. The book can be used by many practitioners such as processing geophysicists, seismic interpreters, geologists, reservoir engineers, petrophysicist, geostatistians, asset mangers and technology application professionals. It will also be of interest to academics to assess the importance of, and contribute to, R&D efforts in relevant areas.

CONTENTS
FOREWORD
PREFACE
ABOUT THE EDITORS
LIST OF CONTRIBUTORS
Part 1. Introduction: Fundamentals of Soft Computing
1 SOFT COMPUTING FOR INTELLIGENT RESERVOIR CHARACTERIZATION AND MODELING
2 FUZZY LOGIC
3 INTRODUCTION TO USING GENETIC ALGORITHMS
4 HEURISTIC APPROACHES TO COMBINATORIAL OPTIMIZATION
5 INTRODUCTION TO GEOSTATISTICS
6 GEOSTATISTICS: FROM PATTERN RECOGNITION TO PATTERN REPRODUCTION
Part 2. Geophysical Analysis and Interpretation
7 MINING AND FUSION OF PETROLEUM DATA WITH FUZZY LOGIC AND NEURAL NETWORK AGENTS
8 TIME LAPSE SEISMIC AS A COMPLEMENTARY TOOL FOR IN-FILL DRILLING
9 IMPROVING SEISMIC CHIMNEY DETECTION USING DIRECTIONAL ATTRIBUTES
10 MODELING A FLUVIAL RESERVOIR WITH MULTIPOINT STATISTICS AND PRINCIPAL COMPONENTS
Part 3. Computational Geology
11 THE ROLE OF FUZZY LOGIC IN SEDIMENTOLOGY AND STRATIGRAPHIC MODELS
12 SPATIAL CONTIGUITY ANALYSIS. A METHOD FOR DESCRIBING SPATIAL STRUCTURES OF SEISMIC DATA
13 LITHO-SEISMIC DATA HANDLING FOR HYDROCARBON RESERVOIR ESTIMATE: FUZZY SYSTEM MODELING APPROACH
14 NEURAL VECTOR QUANTIZATION FOR GEOBODY DETECTION AND STATIC MULTIVARIATE UPSCALING
15 HIGH RESOLUTION RESERVOIR HETEROGENEITY CHARACTERIZATION USING RECOGNITION TECHNOLOGY
16 EXTENDING THE USE OF LINGUISTIC PETROGRAPHICAL DESCRIPTIONS TO CHARACTERISE CORE POROSITY
Part 4. Reservoir and Production Engineering
17 USING GENETIC ALGORITHMS FOR RESERVOIR CHARACTERISATION
18 APPLYING SOFT COMPUTING METHODS TO IMPROVE THE COMPUTATIONAL TRACTABILITY OF A SUBSURFACE SIMULATION-OPTIMIZATION PROBLEM
19 NEURAL NETWORK PREDICTION OF PERMEABILITY IN THE EL GARIA FORMATION, ASHTART OILFIELD, OFFSHORE TUNISIA
21 ENHANCING GAS STORAGE WELLS DEUVERABHJTY USING INTELLIGENT SYSTEMS
Part 5. Integrated Field Studies
22 SOFT COMPUTING: TOOLS FOR INTELLIGENT RESERVOIR CHARACTERIZATION AND OPTIMUM WELL PLACEMENT
23 COMBINING GEOLOGICAL INFORMATION WITH SEISMIC AND PRODUCTION DATA
24 INTERPRETING BIOSTRATIGRAPHICAL DATA USING FUZZY LOGIC: THE IDENTIFICATION OF REGIONAL MUDSTONES WITHIN THE FLEMING FIELD, UK NORTH SEA
25 GEOSTATISTICAL CHARACTERIZATION OF THE CARPINTERIA FIELD, CALIFORNIA
26 INTEGRATED FRACTURED RESERVOIR CHARACTERIZATION USING NEURAL NETWORKS AND FUZZY LOGIC: THREE CASE STUDIES
Part 6. General Applications
27 VIRTUAL MAGNETIC RESONANCE LOGS, A LOW COST RESERVOIR DESCRIPTION TOOL
28 ARTIFICIAL NEURAL NETWORKS LINKED TO GIS
29 INTELLIGENT COMPUTING TECHNIQUES FOR COMPLEX SYSTEMS
30 MULTIVARIATE STATISTICAL TECHNIQUES INCLUDING PCA AND RULE BASED SYSTEMS FOR WELL LOG CORRELATION
AUTHOR INDEX
SUBJECT INDEX

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