Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data for geologically realistic structural models: Patua Geothermal Field case study

Pollack, Ahinoam; Cladouhos, Trenton T.; Swyer, Michael; Siler, Drew L.; Mukerji, Tapan; Horne, Roland N.

doi:10.1016/j.geothermics.2021.102129

Cited by 8 publications

(3 citation statements)

References 35 publications

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“…Data acquisition was carried out at twenty locations, with a distance of about 200 m between each point, forming a straight line. Firstly, the raw magnetic data were corrected according to the International Geomagnetic Reference Field (IGRF), yielding the total magnetic field anomaly [14][15][16]. This was used to obtain a reduction to the pole and upward continuation anomaly map.…”

Section: Methodsmentioning

confidence: 99%

Geothermal System in Parang Wedang, Yogyakarta, Indonesia

Iqbal

Juliarka

2022

J. Eng. Technol. Sci.

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Geothermal manifestations in Parangtritis, Indonesia, known as Parang Wedang Hot Spring, indicate a geothermal system in the subsurface. This circumstance motivated our research to model the Parang Wedang geothermal system in order to determine its subsurface conditions. Geological mapping, the geophysical method, and geochemical analysis were integrated to produce a conceptual model of the Parang Wedang geothermal system. The study area consists of structural hills, karst hills, and eolian plains with andesite breccias, limestone, andesite, and sand deposits as lithological variations. The results of magnetic modeling indicate that the research area is associated with the presence of an andesite intrusion and shows a NE-SW trending geological structure that is thought to be a path for hydrothermal fluid to the surface. Geochemical analysis was performed at two hot springs with temperatures of 47 °C and 49 °C. Geothermometer calculation showed that the geothermal reservoir in Parang Wedang has a temperature of 100 to 120 °C, a depth of about 180 to 285 m, and can be classified as a low enthalpy geothermal system.

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Section: Methodsmentioning

confidence: 99%

Geothermal System in Parang Wedang, Yogyakarta, Indonesia

Iqbal

Juliarka

2022

J. Eng. Technol. Sci.

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“…While Noddy was initially meant for creating simple models for teaching purposes, it has also been used for studying concepts such as geological topology (Thiele et al, 2016), and machine learning techniques (Guo et al, 2021). In addition, it has been used for geophysical inversion (Pollack et al, 2020).…”

Section: Kinematic Modelingmentioning

confidence: 99%

Combining low-temperature thermochronology with 3-D probabilistic kinematic modeling of the Bavarian Subalpine Molasse

Brisson,

Degen,

Wellmann

et al. 2024

Preprint

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To understand the exhumation history of the Alpine foreland, it is important to accurately reconstruct its time-temperature evolution. This is often done employing thermokinematic models. One problem of many current approaches is that they are limited to 2-D and do not consider structural or kinematic uncertainties. In this work, we combine 3-D kinematic forward modeling with a systematic random sampling approach to automatically generate an ensemble of kinematic models in the range of assigned geometric uncertainties. Using Markov chain Monte Carlo, each randomly generated model will be assessed in regards to how well they fit the available thermochronology data. This is done to obtain an updated set of modeling parameters with reduced uncertainty. The resulting, more robust model can then be used to re-interpret the thermochronological data and find alternative drivers of cooling for certain samples.We apply this approach to a simple synthetic model to test the methodology, and then to the Eastern Alps triangle zone in the Bavarian Subalpine Molasse. Results show that it is possible to translate low-temperature thermochronology data into a likelihood function to obtain a 3-D kinematic model with updated, more probable parameters. The thermochronological data by itself, however, may not be informative enough to reduce the parameter uncertainty. The method is useful, however, to study alternative mechanisms of exhumation for the thermochronological samples that are not respected by the modeling, even when uncertainty is considered.

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“…Selecting appropriate tracer is crucial for achieving satisfactory tracer test results. As there are many types of tracers with different functions and properties (Table 2), the selection of tracers is influenced by different thermal reservoir lithology (Liu, 2019;Ren et al 2023;Pollack et al 2021). For example, tracers with acidic aqueous solution should be avoided for carbonate thermal reservoir, while granite thermal reservoirs are prone to reacting with alkaline tracer due to their higher SiO 2 content.…”

Section: Field Testmentioning

confidence: 99%

Research progress on temperature field evolution of hot reservoirs under low-temperature tailwater reinjection

Wang,

Zhou,

Liu

et al. 2024

Journal of Groundwater Science and Engineering

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Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data for geologically realistic structural models: Patua Geothermal Field case study

Cited by 8 publications

References 35 publications

Geothermal System in Parang Wedang, Yogyakarta, Indonesia

Geothermal System in Parang Wedang, Yogyakarta, Indonesia

Combining low-temperature thermochronology with 3-D probabilistic kinematic modeling of the Bavarian Subalpine Molasse

Research progress on temperature field evolution of hot reservoirs under low-temperature tailwater reinjection

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