Full Tensor Gravity Gradiometry Sensitivity Analysis for Delineating Lateral Reservoir Boundaries and Subtle Density Contrasts

Krisna Oka Mahendra; Muhammad Noor Amin Zakariah; Soni Satiawan; Boko Nurdiyanto Suwardi; Edy Widjanarko

doi:10.29017/scog.v49i3.2116

Authors

Krisna Oka Mahendra Universiti Teknologi Petronas
Muhammad Noor Amin bin Zakariah Universiti Teknologi Petronas
Soni Satiawan Universitas Pertamina
Boko Nurdiyanto Suwardi PT. Pertamina Hulu Energi : Upstream Innovation
Edy Widjanarko Balai Besar Pengujian Minyak dan Gas Bumi LEMIGAS

DOI:

https://doi.org/10.29017/scog.v49i3.2116

Keywords:

density contrast, Full Tensor Gravity, gravity modeling, reservoir characterization, SimPEG

Abstract

The gravity method is frequently used for regional basin mapping. However, this method has limitations in resolving rock layers at shallow targets or detecting subtle density contrasts between rock formations in oil and gas exploration. This study investigates the capability of Full Tensor Gravity (FTG) gradiometry to overcome these challenges in sedimentary basin delineation and shallow reservoir characterization. Forward numerical modeling was conducted using the SimPEG Python package to simulate a sedimentary basin containing a reservoir with varying thicknesses (100–500 meters) and rock density contrasts under different saturation conditions. Quantitative analysis demonstrates the superior sensitivity of FTG compared to conventional methods. For a 500-meter-thick gas-saturated reservoir, the horizontal FTG components (Gxx, Gyy) showed an anomaly magnitude change of 66.7%, and the vertical gradient (Gzz) exhibited an increase of 62.5%. These values are higher than the change in the conventional gravity anomaly (Gz), which only reached 52.0%. Furthermore, horizontal gradients effectively delineate the reservoir's lateral boundaries, while the vertical component provides a clearer representation of the overall basin structural geometry. This study confirms that FTG analysis yields a quantitatively improved subsurface model, thereby reducing the ambiguity associated with conventional gravity methods in delineating shallow prospects.

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