Citation: Pratama, W., S. Kita (2022), Stress field orientation obtained from earthquake focal mechanisms
in Indonesia region, Synopsis of IISEE-GRIPS Master’s Thesis.

STRESS FIELD ORIENTATION OBTAINED FROM
EARTHQUAKE FOCAL MECHANISMS IN
INDONESIA REGION
Wahyudi Nasrul Pratama1
MEE21706

Supervisor: Saeko KITA2ABSTRACT

Determination of the stress field is essential to understanding the stress source and earthquake
mechanism. However, the stress field study has been rarely conducted in the Indonesia region. We
constructed the stress map in Indonesia derived from the Global Centroid Moment Tensor (GCMT) andthe National Research Institute for Earth Science and Disaster Prevention (NIED) focal mechanism datafrom 1990 until 2021, where the Agency for Meteorology, Climatology, and Geophysics, Indonesia(BMKG)’s stations were also used for determining focal mechanisms in the NIED catalog. Overall, we
used 3,756 earthquake focal mechanism data with a depth of ≤30 km. We applied two methodologies inthis study; firstly, we created a mesh size of 75 km x 75 km of spatial mean of maximum horizontal
compression stress (SHmax) and fault type. Then, we also performed the stress tensor inversion method
to confirm the spatial mean of SHmax orientations. We got very declivous plunges of 𝜎1 in the northern
North Maluku, southern North Maluku, and Batu-Mentawai-Pagai subduction segments. Meanwhile,
the West and Central Java, the East Java, and the Sumba subduction segments have relatively steeper
plunge angles than other regions. We found that the two methodologies we used yielded the same resultsin general. In our stress map, the orientations of SHmax are commonly perpendicular to the trench inthe subduction zone and subparallel to the plate motion. This stress map also revealed the fault type
distribution, which is generally consistent with the tectonic setting and focal mechanisms of large
earthquakes. We confirmed that the normal faulting associated with SHmax parallel to the trench isintense near the trench of Java and Sumba subduction segments, indicating this area as the uncouple
subduction zone. Stress field map in this study has possibility to assess the potential slip of faults inIndonesia for future prospects.
Keywords: Stress Map, Stress Tensor Inversion, SHmax, Focal Mechanisms.
1. INTRODUCTION
Examination of stress fields is essential for providing knowledge about stress sources and earthquake
mechanics. Several kinds of stress field studies have been conducted in some regions of Indonesia.
However, those studies just examined stress field in limited areas, mostly the western part of Indonesia,
and just a little information about stress fields in the eastern part of Indonesia. Aiming to fill the gap,
this study intends to present the stress orientation in entire Indonesia region. We used earthquake datacatalogs to get the stress orientation because there are many focal mechanism data provided by the
Global Centroid Moment Tensor (GCMT) (Dziewonski et al., 1981; Ekström et al., 2021) and thesource-parameter determinations based on waveform inversion of the Fourier Transformed seismograms(SWIFT) system developed by the National Research Institute for Earth Science and Disaster Prevention(NIED), where the Agency for Meteorology, Climatology, and Geophysics, Indonesia (BMKG)’s
stations were also used for determining focal mechanisms in the NIED catalog (Nakano et al. 2010;
Inazu et al. 2016).

1
2

Agency for Meteorology, Climatology and Geophysics, Republic of Indonesia.
International Institute of Seismology and Earthquake Engineering, Building Research Institute.

12. DATA
We compiled GCMT focal mechanism data from International Seismological Centre (ISC) (Lentas,
2017; Lentas et al., 2019) and the SWIFT system by NIED in this study with the following criteria: We
only used shallow earthquake (≤30 km depth) data to represent the crustal stress with a period from 1990
to 2021 for magnitude (Mw) of 4.3 to 9.0 earthquakes. Focal mechanism data in GCMT were adopted
from 1990 to July of 2007 in our compilation data, because NIED data starts from the middle of 2007.
After that period, we combined both catalogs to increase the number of focal mechanisms for dataprocessing. We considered NIED data as the primary fault orientation because they also used seismic
waveforms from the Indonesia broadband seismograph network by BMKG. In addition, the source
centroid locations were more consistent with the hypocenter determination of USGS compared to
GCMT (Nakano et al., 2010). In total, we used 3,756 events (2,362 events from GCMT and 1,394 eventsfrom NIED) in this study. Then, before inverting the focal mechanisms, we grouped them into smallerareas (Figure 1). In the subduction zone, we used segmentations of the subduction zone in Indonesia
from Irsyam et al. (2017) with some modifications. Besides that, we classified the other regions using
events which have close epicenter distribution and similar focal mechanisms in the majority.

Figure 1. Distribution of compiled focal mechanism data (yellow dots) and area for stress inversions.
Segmentation of subduction zone based on Irsyam et al. (2017) with some modifications.
3. METHODOLOGY
In order to examine the spatial pattern of stress orientation, we adopted a methodology by Imanishi etal. (2019). However, this methodology determines the stress field orientation by calculating the circularmean of SHmax derived from focal mechanism P, B, and T axes in each grid. Therefore, the quality is
not better than the stress inversion result (Heidbach et al., 2010). However, the advantage of this method
is that the spatial distribution of the stress field can be obtained to analyze the heterogeneity of the stressfield in the study area. Therefore, to fulfill the lack of this method, we also performed the stress tensor
inversions in 34 areas in the Indonesian archipelago, using a code by Vavryčuk (2014) as a confirmation.
We adopted Imanishi et al. (2019) methodology to construct a spatial stress mapping forthis study. Firstly, P, T, and B axes from individual earthquake focal mechanisms were converted toSHmax orientation using Zoback (1992) classification. The methodology by Imanishi et al. (2019) also
provides information of the fault type, using a method of Shearer et al. (2006) based on rake angles of
focal mechanisms. Then, we used a 75 km x 75 km mesh considering the amount of data. The stressfield map was constructed using the procedure as follows: (1) take earthquakes within a radius of 100
km around the mesh, (2) if the number of earthquakes in a mesh was equal to or larger than 5, calculate
the weighted average of the SHmax and the fault type value. The weight of each earthquake depends onthe distance from a mesh following Allmendinger et al. (2007), in which we chose 𝛼 equal to 50. Then,2

we used circular statistics for calculating the weighted mean and standard deviation of SHmax at eachmesh (Mardia, 1972).
We converted the stress orientation from inversion method to SHmax, where the orientationof SHmax is better to be used than principal stress direction for displaying tectonic stress results to avoid
an error if the principal stress direction is used. SHmax can be calculated from four stress tensor
inversion parameter results using a procedure by Lund and Townend (2007).
4. RESULTS AND DISCUSSION
The spatial mean of the SHmax and fault type was created using a mesh size of 75 km in both longitude
and latitude directions (Figure 2a). The SHmax orientations are indicated by the straight line and its fault
types are indicated by the background color. Generally, the stress field is perpendicular to the trenchaxis in the subduction zone with dominant thrust faulting. In the Java region, the focal mechanism data
were not so much compared to the subduction region, so the spatial mean of SHmax and fault type was
not too dense. Then, in this region, stress field orientations near the subduction zone were dominantly
parallel to the trench axis associated with normal faulting. This condition also happened in Aru Island,
the south of Bird's Head Region Papua. We also generated the deviation of mean SHmax and fault typefor each mesh (Figures 2b and 2c). In majority, the mean of SHmax standard deviation was less than
40o. The higher standard deviation of SHmax indicated a non-uniformity stress field in that region. The
higher standard deviation for the fault type means that more fault type heterogeneity happened at themesh, which is indicated by yellow to red in Figure 2c.
In case of stress tensor inversion, overall, we used enough data for conducting the stressinversions in the subduction segments (A areas), except in the West Nusa Tenggara subduction segment(A10), in which only 14 pieces of focal mechanism data were available. The 𝜎1 azimuths for each
subduction segment are nearly perpendicular to the trenches, with opposite directions of the subduction
dip, and the azimuths vary for each subduction segment. The plunge angles of 𝜎1 for each subduction
segment vary in the range of 3.36o – 58.68o. The northern North Maluku (A17), the southern North
Maluku (A18), and the Batu-Mentawai-Pagai (A03) subduction segments have very declivous plunges
with 3.39o, 6.68o, and 7.68o, respectively. Meanwhile, the West and Central Java (A07), the East Java
(A08), and the Sumba (A09) subduction segments have relatively steeper plunge angles with 49.56o,
58.68o, and 50.73o, respectively. For the stress ratio R in the subduction zones, all segments produce thestress ratio R close to 1, which indicates compressional stress which is dominant in this area. Then,based on the misfit angles, all segments yield angle less than 45o, indicating the valid result of theinversion. The largest misfit angle occurred in the South Banda subduction segment (A12), with a misfit
angle equal to 31.76o.
On the other hand, in the non-subduction segment (B areas), we conducted stress inversions
in 16 areas (B01 – B16). The minimum number of data that we used for these areas is 20 pieces of focal
mechanism data, namely in the Mamuju fault (B16). The values of stress ratio R vary in B areas.
Dominant extensional stress occurred in several regions, namely the Andaman Sea fault (B01), theSumatera outer-rise (B04), the West-Central Java outer-rise (B05), the East Java outer-rise (B06), theAru trough (B12), the Palu-Koro fault (B12), and the Batui-Balantak fault (B14). In contrast, in the other
B areas compressional stress is dominant. All inversion results showed the valid results according to themisfit angle. The misfit angle for B areas is in the range of 11.51o – 36.42o, with the largest misfit in the
Batui-Balantak fault (B14). We calculated and plotted the azimuth of SHmax from 4 parameters
inversion results based on a mathematical approach of Lund and Townend (2007) (Figure 3a).
In order to confirm those results, we plotted the SHmax azimuths from the methodology of
Imanishi et al. (2019) and SHmax inferred from stress inversions into a map. The small colored rectangle
indicates the spatial SHmax, the colored one indicates the stress regime (normal, strike-slip and thrustfault) in that area, and the long black bars show the SHmax which is derived from the inversions. In
general, those methods reveal the same stress orientation. It must note that the stress orientations frominversion are the regional stress according to inversion area.

3

(a)

(b)

(c)

Figure 2. (a) Spatial mean of SHmax orientation and fault type using a mesh size of 75 km x 75 km.
(b) Standard deviation of the mean SHmax. (c) Standard deviation of the mean fault type.
We confirmed that the normal faulting associated with SHmax parallel to the trench isintense near the trench of Java and Sumba subduction segments, indicating this area as the uncouple
subduction zone (Christensen and Ruff, 1988). This condition is supported by stress tensor inversions
that revealed radial to pure extensive tectonic stress regime in these regions. We also compared thespatial mean fault type map with earthquakes M≥7. The result revealed that our stress map is generally
consistent with focal mechanisms of these large events. It means that the focal mechanisms of future
large earthquakes will be also consistent with this stress map. The most striking discrepancy in focal
mechanism occurred in the Java region, where the thrusting mechanism in 1994 and 2006 Java
earthquakes lie in the strike-slip to normal fault region in our map, these are unusual cases because it isdifficult to create thrust faulting event in the uncouple subduction zone like those in Java region (Bilek
and Engdahl, 2007).
5. CONCLUSIONSThis study has created the stress map for the entire Indonesia derived from the GCMT and NIED focal
mechanism data, filling the gap in the stress field from previous studies. The two methodologies weapplied in this study revealed a good agreement with each other in the SHmax orientation. Overall, theSHmax directions are perpendicular to the trench in the subduction zone and subparallel with platemotion, except in the Java subduction zone, which is dominated by the parallel SHmax orientations to
the trench. In this stress map, we also added information on the spatial mean of fault types which is
generally consistent with the tectonic setting and focal mechanism of large earthquakes in Indonesia.

4

(a)

(b)

(c)

Figure 3. (a) Spatial distribution map of 𝜎1 and 𝜎3 azimuths of inversion result with stress ratio 𝑅 =(𝜎1 − 𝜎2 )/(𝜎1 − 𝜎3 ). (b) SHmax comparison between two methodologies. (c) Comparison between
spatial mean fault type with earthquake focal mechanism M≥7.
We confirmed that near the trench in Java and Sumba subduction segments, they are
dominated by normal faults with the SHmax orientation which is parallel to the trench; in other words,
the tensional stress directions are toward the trench, which is indicated as the uncouple subduction zone.
This condition is consistent with results of stress tensor inversion, which revealed that the plunges of
𝜎1 in this area have relatively larger angles than other subduction segments. If the largest plunge is5

assumed as vertical stress and considering the stress ratio R value, it means that in this subduction
regions, the tectonic stress regimes dominantly are indicated by pure to radial extensive in thesesegments (Delvaux et al., 1997). According to this study, our stress map provides the stress orientations
and fault type mechanisms that can be used for evaluating seismicity in Indonesia. An advanced study
can be done based on this stress map to evaluate the potential of fault slip.
ACKNOWLEDGEMENTS
This research was conducted during the individual study period of the training course “Seismology,
Earthquake Engineering and Tsunami Disaster Mitigation” by the Building Research Institute, JICA,
and GRIPS. I would like to express my sincere gratitude to Dr. Saeko Kita who has supervised andgiven me very useful guidance and advice that carried me through all the stages in this research
project. I would also thank to Kazutoshi Imanishi and Makoto Ohtsubo from AIST for very nicediscussion and suggestion about this research, Yo Fukushima from IRIDeS Tohoku University forhis constructive comments, Václav Vavryčuk from Institute of Geophysics of the Czech Academy of
Science and Björn Lund from Upssala University who have provided codes for stress inversion andSHmax calculation.
REFERENCES
Allmendinger, R. W., Reilinger, R., & Loveless, J., 2007, Tectonics, 26(3).
Bilek, S. L., & Engdahl, E. R., 2007, Geophysical Research Letters, 34(20).
Christensen, D. H., & Ruff, L. J., 1988, Journal of Geophysical Research: Solid Earth, 93(B11), 1342113444.
Dziewonski, A. M., Chou, T.-A., & Woodhouse, J. H., 1981, Journal of Geophysical Research: Solid
Earth, 86(B4), 2825-2852.
Ekström, G., Nettles, M., & Dziewoński, A. M., 2012, Physics of the Earth and Planetary Interiors, 200201, 1-9.
Gephart, J. W., & Forsyth, D. W., 1984, Journal of Geophysical Research: Solid Earth, 89(B11), 93059320.
Heidbach, O., Tingay, M., Barth, A., Reinecker, J., Kurfeß, D., & Müller, B., 2010, Tectonophysics,
482(1), 3-15.
Imanishi, K., Uchide, T., Ohtani, M., Matsushita, R., Nakai, M., 2019, Bull. Geol. Surv. Japan, vol. 70(3), p.273-298.
Inazu, D., Pulido, N., Fukuyama, E., Saito, T., Senda, J., & Kumagai, H., 2016, Earth, Planets and Space,68(1), 73.
Irsyam, M., Widiyantoro, S., Natawidjaya, D. H., Meilano, I., Rudyanto, A., Hidayati, S., Triyoso, W.,
Hanifa, N. R., Djarwadi, D., Faizal, L., Sunarjito, 2017, Pusat Penelitian dan Pengembangan
Perumahan dan Permukiman, Kementerian Pekerjaan Umum dan Perumahan Rakyat
Lentas, K, 2017, Geophysical Journal International, 212(3), 1665-1686.
Lentas, K., Di Giacomo, D., Harris, J., & Storchak, D. A., 2019, Earth Syst. Sci. Data, 11(2), 565-578.
Lund, B., & Slunga, R., 1999, Journal of Geophysical Research: Solid Earth, 104(B7), 14947-14964.
Lund, B., & Townend, J., 2007, Geophysical Journal International, 170(3), 1328-1335.
Mardia, K. V., 1972, Academic Press.
Michael, A. J., 1984, Journal of Geophysical Research: Solid Earth, 89(B13), 11517-11526.
Nakano, M., Yamashina, T., Kumagai, H., & Inoue, H., 2010, Physics of the Earth and Planetary
Interiors, 183(3-4), 456-467.
Shearer, P. M., Prieto, G. A., & Hauksson, E., 2006, Journal of Geophysical Research: Solid Earth,111(B6).
Vavryčuk, V., 2014, Geophysical Journal International, 199(1), 69-77.

6