Interpretation of residual gravity anomaly caused by simple shaped bodies using very fast simulated annealing global optimization

AbstractA very fast simulated annealing (VFSA) global optimization is used to interpret residual gravity anomaly. Since, VFSA optimization yields a large number of best-fitted models in a vast model space; the nature of uncertainty in the interpretation is also examined simultaneously in the present study. The results of VFSA optimization reveal that various parameters show a number of equivalent solutions when shape of the target body is not known and shape factor ‘q’ is also optimized together with other model parameters. The study reveals that amplitude coefficient k is strongly dependent on shape factor. This shows that there is a multi-model type uncertainty between these two model parameters derived from the analysis of cross-plots. However, the appraised values of shape factor from various VFSA runs clearly indicate whether the subsurface structure is sphere, horizontal or vertical cylinder type structure. Accordingly, the exact shape factor (1.5 for sphere, 1.0 for horizontal cylinder and 0.5 for vertical cylinder) is fixed and optimization process is repeated. After fixing the shape factor, analysis of uncertainty and cross-plots shows a well-defined uni-model characteristic. The mean model computed after fixing the shape factor gives the utmost consistent results. Inversion of noise-free and noisy synthetic data as well as field data demonstrates the efficacy of the approach

Inversion of Amplitude from the 2-D Analytic Signal of Self-Potential Anomalies

In the present study, analytic signal amplitude (ASA) or total gradient (TG) inversion of self-potential anomalies has been carried out using very fast simulated annealing (VFSA) global optimization technique. The results of VFSA optimization demonstrate the application and efficacy of the proposed method for idealized synthetic hypothetical models and real single and multiple geological structures. The model parameters deciphered here are the amplitude coefficient (k), horizontal location (x0), depth of the body (z), and shape (q). Inversion of the model parameter suggests that constraining the horizontal location and the shape factor offers the most reliable results. Investigation of convergence rate, histogram, and cross-plot examination suggest that the interpretation method developed for the self-potential anomalies is stable and the model parameters are within the estimated ambiguity. Inversion of synthetic noise-free and noise-corrupted data for single structures and multiple structures in addition to real field information exhibits the viability of the method. The model parameters estimated by the present technique were in good agreement with the real parameters. The method has been used to invert two field examples (Sulleymonkoy anomaly, Ergani, Turkey, Senneterre area of Quebec, Canada) with application of subsurface mineralized bodies. This technique can be very much helpful for mineral or ore bodies investigation of idealized geobodies buried within the shallow and deeper subsurface

Global nonlinear optimization for the estimation of static shift and interpretation of 1-D magnetotelluric sounding data

In the presence of conducting inhomogeneities in near-surface structures, apparent resistivity data in magnetotelluric sounding can be severely distorted. This is due to electric fields generated from boundary charges on surficial inhomogeneities. Such distortion persists throughout the entire recording range and is known as static shift in magnetotellurics. Frequencyindependent static shifts manifest as vertical, parallel shifts that occur in plots of the dual logarithmic scale of apparent resistivity versus time period. The phase of magnetotelluric sounding data remains unaffected by the static shift and can be used to remove the static shift to some extent. However, individual inversion of phase data yields highly nonunique results, and alone it will not work to correctly remove the static shift. Inversions of uncorrected magnetotelluric data yield erroneous and unreliable estimations, while static-shift-corrected magnetotelluric data provide better and reliable estimations of the resistivities and thicknesses of subsurface structures. In the present study, static shift (a frequencyindependent real constant) is also considered as one of the model parameters and is optimized together with other model parameters(resistivity and thickness) using the very fast simulated annealing global inversion technique. This implies that model parameters are determined simultaneously with the estimate of the static shift in the data. Synthetic and noisy data generated for a number of models are interpreted, to demonstrate the efficacy of the approach to yield reliable estimates of subsurface structures when the apparent resistivity data are affected by static shift. Individual inversions of static-shift-affected apparent resistivity data and phase data yield unreliable estimations of the model parameters. Furthermore, the estimated model parameters after individual data inversions do not show any systematic correlations with the amount of static shift in the data. The present study shows that only joint inversion of the apparent resistivity and phase data, without or with optimizing of the static shift, yields models that show good fits between the observed and the model data. Joint inversion results also reveal a systematic relationship between the estimated model parameters and the static shift in the data. The proposed approach also shows that estimated resistivities are ‘S’ (the static shift parameter) times the actual resistivities, and that estimated thicknesses are √S times the actual thicknesses without optimization of the static shift. This result is in good agreement with the existing relationship in the literature. Therefore, the global optimization procedure developed can be effectively used to optimize the static shifts in data, to obtain reliable estimations of model parameters. Subsequently, joint inversion of the apparent resistivity and phase data, with optimization of the static shift, is performed, which yields accurate estimates of subsurface structures. It is demonstrated that this approach can also be used when the data is not affected by the static shift. In such cases, the estimated static shift parameter ‘S’ will be close to unity. The efficacy of the approach is demonstrated with a field example from Singhbhum craton, eastern India, by providing an accurate estimation of the craton thickness and the conducting structure that lies below the craton

Integrating Apparent Conductance in Resistivity Sounding to Constrain 2D Gravity Modeling for Subsurface Structure Associated with Uranium Mineralization across South Purulia Shear Zone, West Bengal, India

South Purulia Shear Zone (SPSZ) is an important area for the prospect of uranium mineralization and no detailed geophysical investigations have been carried out in this region. To delineate the subsurface structure in the present area, vertical electrical soundings using Schlumberger array and gravity survey were carried out along a profile perpendicular to the SPSZ. Apparent conductance in the subsurface revealed a possible connection from SPSZ to Raghunathpur. The gravity model reveals the presence of a northerly dipping low density zone (most likely the shear zone) extending up to Raghunathpur under a thin cover of granitic schist of Chotanagpur Granite Gneissic Complex (CGGC). The gravity model also depicts the depth of the zone of density low within this shear zone at ~400 m near Raghunathpur village and this zone truncates with a steep slope. Integration of resistivity and gravity study revealed two possible contact zones within this low density zone in the subsurface at depth of 40 m and 200 m. Our study reveals a good correlation with previous studies in Raghunathpur area characterized by medium to high hydro-uranium anomaly. Thus the conducting zone coinciding with the low gravity anomaly is inferred to be a possible uranium mineralized zone

Correlation of VLF-EM Data with Radiometric Measurements: Implications for Uranium Exploration around Beldih, South Purulia Shear Zone, India

This study is an attempt to correlate VLF-EM data with the radiometric measurements to decipher the subsurface structure and to locate uranium mineralization in the shear zone. The study area is around Beldih mine which is an open cast apatite mine located on the South Purulia Shear Zone. VLF method has been applied to map the structure and the presence of radioactive minerals has been delineated by the detection of high α and γ counts with respect to the background radiations. High radiation counts and high surface γ activity are found just above the higher apparent current-density zones in all the profiles studied, at various locations, indicating uranium and/or thorium mineralization as well as good correlation between these techniques

Inversion and Uncertainty Estimation of Self-Potential Anomalies over a Two-Dimensional Dipping Layer/Bed: Application to Mineral Exploration, and Archaeological Targets

Self-Potential data have been widely used in numerous applications. The interpretation of SP data from subsurface bodies is quite challenging. The advantages of geophysical inversion for interpreting non-linear geophysical problems have gained a great deal of attention over conventional interpretation. The efficiency of the present inversion approach in interpreting SP anomalies from a thin dipping layer/bed is presented in the study. The inversion approach was applied to interpret synthetic model parameters such as the self-potential of the layer (k), depth to the body top (h), location of the body (x0), dip angle (θ), and the upper and lower end of the sheet (δ1 and δ2). The interpretation of the results showed that the parameters Δh, δ1, and δ2 exhibited a wide range of results. The estimated parameter values lay within the limit of uncertainty. The inversion approach was also applied to two field datasets obtained from polymetallic deposits in Russia and Azerbaijan for mineral exploration purposes and one from a buried ancient Roman limestone construction in Halutza, Israel, for the purposes of archaeological study. The field investigation results demonstrate a good agreement with previous works of literature. The efficiency of the present approach for interpreting SP anomalies from thin layer/bed-like structures is shown in this study

Global nonlinear optimization for the interpretation of source parameters from total gradient of gravity and magnetic anomalies caused by thin dyke

An efficient approach to estimate model parameters from total gradient of gravity and magnetic data based on Very Fast simulated Annealing (VFSA) has been presented. This is the first time of applying VFSA in interpreting total gradient of potential field data with a new formulation estimation caused due to isolated causative sources embedded in the subsurface. The model parameters interpreted here are the amplitude coefficient (k), exact origin of causative source (x0) depth (z0) and the shape factors (q). The results of VFSA optimization show that it can uniquely determine all the model parameters when shape factor is constrained. The model parameters estimated by the present method, mostly the shape and depth of the buried structures were found to be in excellent agreement with the actual parameters. The method has also the proficiency of evading highly noisy data points and improves the interpretation results. Study of histogram and cross-plot analysis also suggests the interpretation within the estimated uncertainty.  Inversion of noise-free and noisy synthetic data for single structures as well as field data demonstrates the efficacy of the approach. The technique has been warily and effectively applied to real data examples (Leona Anomaly, Senegal for gravity and Pima copper deposit, USA for magnetic) with the presence of ore bodies. The present method can be extremely applicable for mineral exploration or ore bodies of dyke-like structure embedded in the shallow and deeper subsurface. The computation time for the whole process is very short