Self-Potential Method: Theoretical Modeling and Applications in Geosciences (Springer Geophysics)

✍ Scribed by Arkoprovo Biswas (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 322
• Category: Library

✦ Synopsis

The book deals primarily with the aspects of advances in Self-Potential geophysical data modeling, different interpretation techniques, new ideas and an integrated study to delineate the subsurface structures associated with exploration, contamination, buried paleochannels, archaeological investigations, glaciology, geomorphology, subsurface mapping and also in hydrocarbon exploration.The book is specifically aimed with the state-of-art information regarding research advances and new development in these areas of study, coupled to extensive modelling and field investigations obtained from around the world. It is extremely enlightening for the students, research workers, scientists, faculty members in Applied Geophysics, Near Surface Geophysics, Potential field, Electrical and Electromagnetic methods, Mathematical Modeling Techniques in Earth Sciences, as well as Environmental and other practical problems associated with Earth Sciences.

✦ Table of Contents

Preface
Acknowledgments
Contents
Editor and Contributors
1 Analytical Methods in the Interpretation of Self-Potential Anomalies—A Comprehensive Review
1.1 General Introduction
1.2 Interpretation of SP Anomalies
1.3 Hilbert Transforms
1.4 Analytic Signal and Amplitude
1.5 2-D Horizontal Circular Cylinder
1.6 Spherical Structures
1.7 Hartley Spectral Analysis of SP Anomalies
1.8 Artificial Neural Network Analysis
1.9 Noise Analysis
1.10 Discussion
References
2 Metaheuristics Inversion of Self-Potential Anomalies
2.1 Introduction
2.2 Forward SP Model
2.3 Optimization Methods
2.4 Inversion of Spontaneous Potential (SP) Anomalies
2.4.1 Ambiguity and Non-uniqueness of SP Inverse Solutions
2.4.2 Ambiguity Control
2.4.3 Formulation of the Objective/target Function for SP Problem
2.5 Metaheuristics Inversion of SP Anomalies
2.5.1 Evolutionary Algorithms (EAs)
2.5.2 When Using Metaheuristics?
2.5.3 Examples of the Metaphor Based Algorithms
2.6 Application to Synthetic Model with and Without Noise
2.6.1 Application to Simple Geometrical Models
2.6.2 Application to Thin Sheet Model
2.7 Application to Field Examples
2.7.1 Application to Field Data Approximated by Simple Geometrical Models
2.7.2 Anomalies Approximated by Thin Sheet Model
2.8 Conclusions
References
3 Self-potential Inversion and Uncertainty Analysis via the Particle Swarm Optimization (PSO) Family
3.1 Introduction
3.2 The Streaming Potential Forward and Inverse Problems
3.3 The Inverse Problem and the Topology of the Cost Function
3.4 The PSO Family
3.5 PSO Design in the SP Case
3.6 Modeling the Bogoslovsky and Ogilvy Dataset
3.7 Conclusions
References
4 A Comparison of the Model Parameter Estimations from Self-Potential Anomalies by Levenberg-Marquardt (LM), Differential Evolution (DE) and Particle Swarm Optimization (PSO) Algorithms: An Example from Tamış-Çanakkale, Turkey
4.1 Introduction
4.2 Materials and Methods
4.2.1 Formulation of the SP Anomaly
4.2.2 Algorithms
4.2.3 Differential Evolution (DE) Algorithm
4.2.4 Parameter Estimation Studies
4.2.5 Synthetic Examples
4.2.6 Field Example
4.3 Conclusions
References
5 Estimation of the Buried Model Parameters from the Self-potential Data Applying Advanced Approaches: A Comparison Study
5.1 Introduction
5.2 Methodology
5.2.1 Forward Modeling
5.2.2 Least Squares Inversion Technique
5.2.3 Particle Swarm Optimization
5.2.4 Neural Network Algorithm
5.3 Synthetic Examples
5.3.1 Sphere Model
5.3.2 Horizontal Cylinder Model
5.4 Field Example
5.4.1 Malachite Mine, USA Real Data
5.5 Conclusions
References
6 Determining the Structure Factor and Parameters of a Buried Polarized Structure from Self Potential Anomalies
6.1 Introduction
6.2 Theory of the Method
6.2.1 Determination of X0 and V(0)
6.3 Theoretical and Field Applications
6.4 Conclusion
Appendix: Determination of Roots of Non-linear Equations
Regula False Method
Bisection Method
References
7 Ensemble Kalman Inversion for Determining Model Parameter of Self-potential Data in the Mineral Exploration
7.1 Introduction
7.2 Methodology
7.2.1 Ensemble Kalman Inversion
7.2.2 Forward Modeling
7.2.3 Inversion Using EKI
7.3 Synthetic Model
7.3.1 EKI in Single Anomaly
7.3.2 EKI in Multiple Anomalies
7.4 Field Examples
7.4.1 Neem-Ka-Thana, India
7.4.2 Malachite Mine, Jefferson County, Colorado, USA
7.4.3 Surda Anomaly, Portugal
7.5 Conclusion
References
8 Advanced Analysis of Self-potential Anomalies: Review of Case Studies from Mining, Archaeology and Environment
8.1 Introduction
8.2 Self-potential Observations: Common Disturbances
8.2.1 Different Kinds of Noise in SP Observations
8.3 Review of Quantitative Interpretation Methods
8.4 Some Common Aspects of Magnetic and SP Fields
8.4.1 Quantitative Analysis of SP Anomalies by the Use of Advanced Methodologies Developed in Magnetic Prospecting
8.4.2 SP Observations on an Inclined Profile
8.5 Quantitative Analysis of SP Anomalies
8.5.1 Testing on Theoretical Models
8.5.2 Mining Geophysics
8.5.3 Archaeological Sites
8.5.4 Environmental Geophysics
8.5.5 Technogenic Geophysics
8.5.6 Generalization of the Calculated Self-Potential Moments
8.6 Conclusions
References
9 Preferential Water Flow Pathways Detection in Sinkholes Using Self-Potential (SP) Method. The Study Case of Anina Karst Region (Banat Mountains, Romania)
9.1 Introduction
9.2 Study Area and Investigation Sites Description
9.3 Self-Potential as Geophysical Method
9.4 Methodology
9.5 Results
9.5.1 Mărghitaș Plateau
9.5.2 Colonovăț Plateau
9.5.3 Cârneală Plateau
9.5.4 Brădet Plateau—Culmea Neagră Area
9.6 Discussions and Conclude Remarks
References
10 Interpretation of Self-Potential (SP) Log and Depositional Environment in the Upper Assam Basin, India
10.1 Introduction
10.2 Geology
10.3 Methodology
10.3.1 The Determination of Formation Water Resistivity (Rw)
10.3.2 The Determination of Volume of Shale (Vsh) in the Formations
10.3.3 SP Log Shape Analysis
10.4 Estimation of Petrophysical Parameters
10.4.1 Estimation of Water Saturation in the Formations
10.4.2 Estimation of porosity Φ(s)
10.4.3 Estimating the Types of Shale
10.5 Results and Discussions
10.6 Depositional Environment
10.7 Conclusions
References
11 High Resolution Electrical Resistivity Tomography and Self-Potential Mapping for Groundwater and Mineral Exploration in Different Geological Settings of India
11.1 Introduction
11.2 Interpretation of 2D Inverted Resistivity and Induced Polarization Models
11.2.1 Results and Discussions
11.3 Conclusions
References