Gravity observation of field camp geophysics in Karangsambung using Data Acquisition 2005-2019

The study of field camp geophysics in Karangsambung has been done since 1996 until 2019 by geophysical engineering ITB. During the field activities, students was assigned with several data acquisition using various geophysical methods. One of the most common method to conducted alongside with surface geological mapping is gravity. Compilation of gravity data during the activities will be presented in this work. There are two categories of data compilation during 24 years: data compilation 1996-2004, and 2005-2019. The observation conducted using relative gravimeter with data distribution already cover geological surface map in the study area (Luk-Ulo Melange Complex, Karangsambung Formation, Totogan Formation, and Diabas Intrusion). The pattern of gravity observation shows correlated with topographic variation. Range gravity observation from this study is about 62 mGal.

A High-Sensitivity, Low-Drift MEMS Relative Gravimeter for Multi-Pixel Imaging Applications

<p><strong>Novelty / Progress Claim(s)</strong></p><p>This paper reports a capacitive readout-based MEMS relative gravimeter which can detect sub-Hz microseismic and slowly varying gravitational Earth tide signals. The gravimeter has a noise floor of 6-7 uGal/rt(Hz) at 1Hz and a linear drift of <250 uGal/day, metrics which are on a par with the commercially available gravimeters, and are leading in the field of MEMS accelerometers. The gravimeter is packaged in a standard ceramic-carrier and interfaced to a low-power, advanced FPGA-based readout. This setup is housed within a bespoke thermal enclosure, making the platform ideal for multi-pixel array-based implementation in the field.</p><p><strong>Background/State-of-the-Art</strong></p><p>Gravimeters are used to measure the local acceleration due to gravity (g). One of the emerging applications of gravimetry is in volcanology where gravimeters can be used to understand magma plumbing, providing information on volcanic activity/unrest events. However, this requires multi-pixel ‘gravity-imaging’ around volcanoes, a feat which is not possible using the expensive, complex, and large form-factor commercially available gravimeters.</p><p>Recently, researchers have developed MEMS-scale accelerometers which have excellent sensitivities but not yet demonstrated good long-term stability, making them non-viable for long-term monitoring of slow gravity changes (such as produced by magma flow). In a previous work, the authors have demonstrated an optical shadow-sensor readout based MEMS gravimeter with a sensitivity of 40 uGal/rt(Hz). Building on the work, a portable version of the gravimeter was also reported previously. The devices in both the setups were limited by the displacement noise of the optical shadow-sensor and the packageability of the setup.</p><p>In this paper, we are reporting a novel gravimeter which uses a capacitive-readout for sensing the proof-mass displacement, is embedded in a MEMS IC package, and uses advanced FPGA-based electronics for signal conditioning. The improved displacement sensitivity of the capacitive readout allows designing stiffer suspension-springs making the device more robust for operations in extreme environments. The acceleration sensitivity achieved using the new gravimeter is around 6-7 uGal/rt(Hz) at 1Hz, which is a significant improvement over the previous versions of the gravimeter. The device is currently being readied for field trials in the sectors of volcano gravimetry and oil & gas, showing the maturity of the technology.</p><p><strong>Methodology</strong></p><p>The reported gravimeter has a microfabricated silicon proof-mass which is suspended from thin flexures. Metal-combs are patterned on top of the proof-mass and a fixed glass layer with complementary combs is assembled to be at a close separation from the proof-mass. The overlapping combs act as a capacitor, the magnitude of which is dependent on the proof-mass displacement. The multi-layered gravimeter is embedded within a standard 32-pin ceramic DIP chip-carrier and wire bonded. The MEMS package is interfaced with analog signal conditioning electronics and a digital lock-in implementation is employed for converting the capacitance change into useful units (uGals).The electronics noise of the setup is measured to be <1 uGal. To reduce temperature-related effects, a mK active temperature control is implemented around the device. The packaged device is housed within a prototype thermal enclosure making the platform field-portable.</p>

pyGABEUR-ITB: A FREE SOFTWARE FOR ADJUSTMENT OF RELATIVE GRAVIMETER DATA

<p class="JUDUL">pyGABEUR-ITB (Python<em> GayaBEUrat Relatif – Institut Teknologi Bandung)</em> is a free and interactive software for adjustment of relative gravimeter data, developed based on Python programming language. pyGABEUR-ITB can adjust relative gravity measurements and provide reliable estimates for correcting instrument’s systematic errors, such as gravimeter drift. Furthermore, pyGABEUR-ITB can also detect possible outliers in the observations using the t-criterion method. Since pyGABEUR-ITB is using the weighted constraint adjustment, at least one fixed station is required accordingly. Relative gravimeter data around Palu-Donggala area (Central Sulawesi) observed by Center for Geodesy Control Networks and Geodynamics, Geospatial Information Agency, were used to test the performance of pyGABEUR-ITB. The processing results were then compared against those calculated using GRAVNET software. The comparisons show that both pyGABEUR-ITB and GRAVNET softwares statistically provide simillar results, with the total RMS value of about 5 mGal. In term of computer’s requirement, pyGABEUR-ITB can be excecuted under a computer with the following minimal requirements: x64 CPU, 1 GB memory and WINDOWS 7 OS. Finally, it is important to mention that pyGABEUR-ITB is recently suited to process the data from the gravimeter that adopts the principle of vertical spring balance. In the near future, pyGABEUR-ITB will be extended to be able to automatically adapt to various observation principles.</p><strong></strong>