Abstract

A comprehensive workflow was developed for the advanced analysis and interpretation of recently acquired Airborne Gravity Gradiometry (AGG) data in Karewa Basin for the first time. This was achieved by creating a Python-based program encompassing a full suite of data handling techniques, including data loading, quality control, multiquadric interpolation, and robust visualization. A key aspect of this work is the separation of regional and residual components using a 6th order Butterworth filter, enabling the isolation of shallow anomalies relevant to exploration. Two advanced density inversion techniques were employed: a 2D model-based inversion utilizing a hybrid Preconditioned Conjugate Gradient with Bat Algorithm (PCG-BAT) for gravity data inversion, and a high-resolution 3D density imaging technique based on Fourier Domain Transformations of gravity and Full Tensor Gravity (FTG) data. The 2D inversion, constrained by a priori geological model derived from field data, revealed an undulating basement with variations in sedimentary thickness, indicative of a compressional regime. The 3D density inversion produced a detailed volumetric model of the subsurface, from which eight density profiles were extracted. These profiles has brought out the prominent NE-SW oriented significant variations in the thickness of Karewa sediments and high-density anomalies corresponding to the Panjal volcanics, some of which were validated & corroborated with existing well data. The results substantiate significant compressional deformation within the basin during Himalayan Orogeny and revealed the sub-surface strati-structural dispositions. These promising results may further utilize to evaluate the hydrocarbon potential of the Basin in conjugation with other G&G study.