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Identifying Geological Fault Structures Using GGMplus Satellite Data and Derivative Method, Study Guides, Projects, Research of Geotechnical Engineering

This title describes a research project using satellite gravity data (and derived information) to create a 3D model of the subsurface geological structures, specifically fault systems, beneath the Mount Endut geothermal area. The goal is to better understand the geothermal systems by identifying and characterizing these faults.

Typology: Study Guides, Projects, Research

2024/2025

Available from 06/21/2025

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GEOMATICS AND ENVIRONMENTAL ENGINEERING
IDENTIFYING GEOLOGICAL FAULT STRUCTURES
USING GGMPLUS SATELLITE DATA AND DERIVATIVE
METHODS TO CHARACTERIZE MOUNT ENDUT
GEOTHERMAL SYSTEMS
VIA 3D-INVERSION GRAVITY MODELING
Abstract:
The geological map shows that the Mount Endut area possesses a
geothermal system, which is suggested by the presence of
geothermal surface manifestations: the Cika- wah and
Handeleum hot springs. The existence of a subsurface geological
fault struc- ture along the manifestations creates good
permeability for the geothermal reser- voir. The purpose of this
study was to utilize Global Gravity Model plus (GGMplus)
gravity satellite data to prove the existence of a geological fault
structure around the manifestation area with the first horizontal
derivative (FHD) and second vertical derivative (SVD) methods;
then, we developed a conceptual model of the geothermal system
from the 3D-inversion gravity method. Results show a cap
suspected of being clay, with a density of 2.522.58 g/cm3 at
depth of 01250 m. The reservoir layer was suspected to be lava
rock with a density of 2.602.66 g/cm3 at a depth of 15003000
m; also, the heat source layer was suspected to be an igneous
intrusion with a density of 2.702.72 g/cm3 at depth of 1750
3000 m.
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GEOMATICS AND ENVIRONMENTAL ENGINEERING

IDENTIFYING GEOLOGICAL FAULT STRUCTURES

USING GGMPLUS SATELLITE DATA AND DERIVATIVE

METHODS TO CHARACTERIZE MOUNT ENDUT

GEOTHERMAL SYSTEMS

VIA 3D-INVERSION GRAVITY MODELING

Abstract:

The geological map shows that the Mount Endut area possesses a

geothermal system, which is suggested by the presence of

geothermal surface manifestations: the Cika- wah and

Handeleum hot springs. The existence of a subsurface geological

fault struc- ture along the manifestations creates good

permeability for the geothermal reser- voir. The purpose of this

study was to utilize Global Gravity Model plus (GGMplus)

gravity satellite data to prove the existence of a geological fault

structure around the manifestation area with the first horizontal

derivative (FHD) and second vertical derivative (SVD) methods;

then, we developed a conceptual model of the geothermal system

from the 3D-inversion gravity method. Results show a cap

suspected of being clay, with a density of 2.52–2.58 g/cm

3

at

depth of 0 – 1250 m. The reservoir layer was suspected to be lava

rock with a density of 2.60–2.66 g/cm

3 at a depth of 1500 – 3000

m; also, the heat source layer was suspected to be an igneous

intrusion with a density of 2.70–2.72 g/cm

3

at depth of 1750–

3000 m.

of subsurface conditions [12, 13].

This research conducted a fault analysis that controlled the

manifestation of Cikawah and Handeleum and carried out 3D modeling using

the gravity method on satellite data that originated from GGMplus.

2. Materials and Method

The gravity method is widely used to identify the presence of

geologi- cal faults [20] as well as the rocks that make up a geothermal

system. However, identifying the presence of fault structures requires

supplementary techniques to offer a clearer representation, so further

methods are needed in order to provide a clear picture; namely, by using

the FHD and SVD methods to further refine fault- boundary detection.

This research was conducted to prove the existence of a fault that controlled

the

manifestation of Cikawah and Handeleum and carried out 3D-inversion

modeling

Identifying Geological Fault Structures Using GGMplus Satellite Data... 3

3

using the gravity method on data that originated from GGMplus. Several

scientific and engineering applications require high-resolution and largely

complete gravi- ty knowledge; this is now available through GGMplus

gravity data [7]. A research flowchart is shown in Figure 1.

Fig. 1. Research flowchart

2.1. Geological Sefling

The morphology of the Mount Endut is classified into four units:

complex cone (35%), volcanic cone (25%), weakly undulating hill (32%),

Identifying Geological Fault Structures Using GGMplus Satellite Data... 5

5

is as follows: the Baduy sediment member unit (Tmd), the Bojongmanik

sediment member unit (Tmb), Andesitic intrusion (Ta), Pre-Endut

volcanic rock (Tlpe), Mt. Kendeng lava breccia (Tbr), Mt. Pilangranal lava

(Tlr), Diorite (Td), Granodio- rite (Tgr), Mt. Pilar breccia lava (Qbp), Mt.

Pilar lava (Qlp), Endut lava 1 (Qle1), En- dut Pyroclastic Flow (Qae), Endut

lava 2 (Qle2), Endut lava breccia (Qbe), Endut Lava 3 (Qle3), and Alluvium

(Qal). The geological structure of the Mount Endut area is manifested by the

presence of hill alignments (lineaments), volcanic cones, topo- graphic

alignments, triangular facets, fault scarps, joints, rock offsets, and fault mir-

rors (slickensides) as well as the emergence of geothermal manifestations

and al- tered rocks (Fig. 2). In several areas, Mount Endut has limestone

facies that generally deposit in marine environments. Based on the

geological map of the Leuwidamar Sheet, the limestone facies in the study

area are part of the Bojongmanik and Badui Formations and are in the Bogor

Physiographic Zone [22]. The geothermal manifes- tations of Mount Endut

are in the forms of hot springs that appear at several man- ifestation

locations in the Cikawah and Handeuleum areas (located at the western foot

of Mount Endut) [23].

Fig. 2. Geological map of Mount Endut

Source: [21]

modeling using SRTM (Shuttle Radar Topography Mission) global

topography. ERTM has a spatial scale with a spherical harmonic coefficient

of up to 2160 degrees, which is used in making GGMplus gravity maps on

short scales from 10 km to 250 m [25, 26].

In selecting GGMplus for the gravity-data analysis in this study, several

addi- tional factors beyond those that were mentioned before warranted

consideration. First, GGMplus offers a global gravity-field model that is

continuously updated, thus ensuring that the data reflects the most current

understanding of our gravita- tional variations. This is particularly important

in geothermal studies, where sub- tle changes in gravity can indicate the

presence of geothermal reservoirs or fault lines [27, 28]. Furthermore,

GGMplus incorporates a multi-resolution approach, thus allowing for the

integration of both high-resolution local data and broader re- gional data sets

[29]. This capability enables researchers to analyze gravity anoma- lies at

various scales, thus facilitating a more comprehensive understanding of the

geological context.

Identifying Geological Fault Structures Using GGMplus Satellite Data... 9

9

Additionally, GGMplus provides access to a wealth of ancillary data,

including topographic and geological information (which can be crucial for

interpreting gravity anomalies of surface features) [6, 30]. The software also

supports advanced filtering techniques that can enhance the clarity of the

gravity data by minimizing noise and artifacts, thus improving the accuracy

of subsequent analyses [31]. Moreover, the user-friendly interface of

GGMplus allows for efficient data manipulation and visu- alization, making

it easier for researchers to communicate their findings and engage

interactively with the data [32]. Last, the strong community support and

extensive documentation that are associated with GGMplus foster a

collaborative environ- ment for researchers, thus enabling them to share

insights and methodologies that can enhance the overall quality of

geophysical research. These factors collectively underscore the rationale for

choosing GGMplus as a pivotal tool in the investigation of the geothermal

systems at Mount Endut.

Traditional gravity methods, which typically entail the collection of

gravity data from ground stations, can be labor-intensive and have limited

spatial coverage. In contrast, GGMplus integrates satellite data, thus

providing a more comprehen- sive view of gravitational anomalies across

vast areas without the need for extensive ground surveys. This capability is

crucial for the preliminary mapping and under- standing of geological

features before conducting more-invasive ground-based in- vestigations [33,

34]. For example, GGMplus data has been successfully utilized in studies

that have identified geothermal systems and fault structures, thus demon-

strating its effectiveness in enhancing traditional methodologies [27, 35].

2.3. Data Corrections

The data that was obtained when downloading from GGMplus was still

in the form of gravity disturbances and not yet in the form of a free-air

Identifying Geological Fault Structures Using GGMplus Satellite Data... 11

11

Free-Air-Anomaly Correction

Free-air-anomaly correction has an influence that originates from a

gravity dis- turbance (δg). To get the free-air anomaly at a specific position,

it is necessary to correct any free-air anomalies.

The following is the formula for finding free-air-anomaly values [37]:

FAA 0.3086 h g FAC g (2)

where

: FAA – free-air anomaly [mGal],

FAC – free-air correction [mGal],

δ g – gravity disturbance value from GGMplus data [mGal],

h – altitude or elevation value that is obtained from geoid [m].

Terrain Correction

Terrain correction is a correction that is caused by the differences in

irregular topographical forms at measurement points, such as mountains,

hills, and valleys; this affects the gravity value that is obtained. For this

reason, terrain corrections are carried out in order to obtain a value that is

close to the rock configuration [33]. Terrain corrections can be obtained

using the Hammer chart method or DEM (digital elevation model) maps.

The calculations of terrain corrections in this study used Geosoft software by

entering the data in the form of coordinates ( X , Y ) and DEM.

The following is the equation for field corrections [38]:

TC G ( r

r )

where:

TC – field correction [mGal],

G – Newton’s gravitational constant [Nm

2

/kg

2

] ( G = 6.67430∙ 10

− 11

r

2  z

2

rz



Nm

2 /kg

2 ),

ρ – rock density [kg/m

3 ],

θ – angle formed [°],

r 1

  • radius of inner circle [m],

r 2

  • radius of outer circle [m],

z – altitude/depth of field [m] (an absolute difference between the

station

elevation and the average elevation ( z = | z stations

z average

This equation estimates the gravitational effect of the terrain in each

sector of the Hammer chart; the total terrain corrections are obtained by

summing up the con- tributions from all of the sectors. The average altitude

within a single compartment is estimated from the contour lines within this

compartment and then subtracted from the station altitude. The difference in

altitude ( z ) is used to calculate the terrain- correction contribution for each

compartment. To obtain the total terrain correction, we summed up all of the

contributions from the innermost sector to the outermost sector, resulting in

the final terrain correction value.

Complete Bouguer Anomaly Correction

Complete Bouguer anomaly (CBA) correction is the sum of the simple

Bouguer anomaly and terrain corrections. CBA describes the density

conditions below the surface of the study area (which later requires

separations between the regional and residual anomalies for further analysis)

[39]. The following is the equation for ob- taining CBA correction:

CBA SBA TC (6)

where

: CBA – complete Bouguer anomaly

[mGal], SBA – simple Bouguer

anomaly [mGal], TC – terrain

correction [mGal].

Identifying Geological Fault Structures Using GGMplus Satellite Data... 15

15

z (^) 0

2.4. Energy Spectrum Analysis

Spectrum analysis is performed to separate regional and residual

anomalies so that the estimated depth of an anomaly can be determined.

This analysis is done with the Fourier transform, which is used to convert

time-domain data into a fre- quency domain. Systematically, the spectrum

value results from the gravitational potential derivative in the horizontal

plane. The Fourier transform can be written with the following equation

[39]:

F [ g ] 2 G e

| k |( z 0

z )

with z′ > z (7)

where:

F [ g z

] – Fourier transform of gravitational acceleration derivative

(vertical component) [s

  • 2 ],

G – Newton’s gravitational constant [Nm

2 /kg

2 ] ( G = 6.67430 ∙ 10

− 11

Nm

2

/kg

2

),

μ – body mass [kg],

z 0

  • height of measurement point [m],

z ′ – anomaly depth [m].

The processing of the energy-analysis data uses Oasis Montaj software

to pro- duce a radially averaged power spectrum (RAPS) curve from the

Fourier transform process, which is displayed in the logarithmic value of the

normalized energy spec- trum at each radial frequency value. To carry out a

depth analysis with wave num- ber ( k ) and amplitude ( A ) values, it can be

done to separate the regional and resid- ual anomalies by determining the

cutoff area of the existing spectrum analysis [39].

2.5. Bandpass Filters

A gravity anomaly is the sum of the sources of an anomaly under a

surface [40]; so, it is necessary to separate the regional anomaly, residual

Identifying Geological Fault Structures Using GGMplus Satellite Data... 17

17

of the geological structure of the gravity anomaly. The FHD-value equation is

ob- tained from the following equation [43]:

FHD (8)

where ∂ g /∂ x and ∂ g /∂ y are the first derivatives of the gravity anomaly in the

x and y directions, respectively. In cross-sectional modeling, only the x

direction is used; so, this formulation is as follows:

g

FHD

x

(9a)

This equation can be written as follows:

g

g ( i 1)

g i

,

x x

g g

FHD

( i 1) i

x

(9b)

where

: FHD – first horizontal

derivative,

g – anomalous value [mGal],

x – difference in distance along the track [m].

Second Vertical Derivative (SVD)

SVD is used in interpreting structures that are insufficient in the Bouguer

  g

2

 (^)  g

2

 

  (^)  

x

  

y

anom- aly map to separate the shallow and deep structural effects that result

in regional and residual anomalies. A residual anomaly describes a structure

that is close to the surface but has not provided specific results; therefore, a

second vertical descent is needed for a more specific structural effect [44].

This second vertical descent is a high-pass filter that provides a clear

picture of the residual anomalies in shallow structures; therefore, SVD is

used to identify the type of down fault or up fault. In the SVD method, the

existence of a fault boundary is indicated by an SVD value of zero (or close

to zero). The SVD equation is obtained through the horizontal deriv- ative

using the Laplace equation for gravity anomalies; namely, the following

[18]:

g 0 ,

2

g

2

g

2

g

x

2 y

2 z

2