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Hendra Grandis
Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132
Engineering

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A Note on the Use of the Second Vertical Derivative (SVD) of Gravity Data with Reference to Indonesian Cases Prihadi Sumintadireja; Darharta Dahrin; Hendra Grandis
Journal of Engineering and Technological Sciences Vol. 50 No. 1 (2018)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2018.50.1.9

Abstract

Gravity data analysis and interpretation are based, among others, on their spatial variation represented by horizontal and vertical gradients. The gradient or derivative of a gravity field can be calculated either in the spatial domain or the wave-number domain. Historically, the second vertical derivative (SVD) of gravity data can be used to delineate the boundaries of anomalous sources. This paper addresses inappropriate use of the SVD of gravity data, with reference to current practices in Indonesia. The SVD's relative magnitude along a profile is widely used to define whether a density contrast and its dipping orientation correspond to a normal or reverse fault, which may be geologically incorrect. Furthermore, the SVD is calculated by approximation using the horizontal derivative, which may be erroneous especially with poorly distributed data and anomalous 3D sources. We exemplify our analysis with synthetic data and propose a more appropriate spectral-based analysis using field data.
Layer Stripping in Magnetotellurics (MT) for Enhancement of Resistivity Change Effect in Reservoir: Equivalence Analysis Hendra Grandis; W Warsa; Prihadi Sumintadireja
Journal of Engineering and Technological Sciences Vol. 52 No. 2 (2020)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2020.52.2.9

Abstract

Magnetotellurics (MT) can be applied to monitor resistivity change at depth that is for example due to fluid injection in enhanced oil recovery or CO2 storage. The observed MT data changes at the surface may be insignificant, but the effect can be enhanced using the layer stripping method, i.e. calculating MT data changes that would be observed at depth based on data from the surface. Two well-known formulas for MT 1D forward modeling were reformulated to allow for calculation of the impedance at depth based on the impedance at the surface. We applied the layer stripping technique to synthetic data associated with models that were representative of a likely CO2 storage site. We also used an equivalent model and the Monte Carlo approach to estimate the sensitivity of the method to cope with the uncertainty of the host model and the input data. The layer stripping calculation has the greatest uncertainty at short periods, where the real and imaginary parts of the complex impedance tend to be equal, i.e. an homogeneous medium response. The layer stripping technique should be used with great caution based on a relatively precise 1D host model.
Co-Authors Darharta Dahrin Prihadi Sumintadireja Prihadi Sumintadireja Warsa warsa