scholarly journals Structures and fluid flows inferred from the microseismic events around a low-resistivity anomaly in the Kakkonda geothermal field, Northeast Japan

Geothermics ◽  
2022 ◽  
Vol 100 ◽  
pp. 102320
Author(s):  
Kyosuke Okamoto ◽  
Kazutoshi Imanishi ◽  
Hiroshi Asanuma
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kyosuke Okamoto ◽  
Hiroshi Asanuma ◽  
Hiro Nimiya

AbstractSubsurface structure survey based on horizontal-to-vertical (H/V) spectral ratios is widely conducted. The major merit of this survey is its convenience to obtain a stable result using a single station. Spatial variations of H/V spectral ratios are well-known phenomena, and it has been used to estimate the spatial fluctuation in subsurface structures. It is reasonable to anticipate temporal variations in H/V spectral ratios, especially in areas like geothermal fields, carbon capture and storage fields, etc., where rich fluid flows are expected, although there are few reports about the temporal changes. In Okuaizu Geothermal Field (OGF), Japan, dense seismic monitoring was deployed in 2015, and continuous monitoring has been consistent. We observed the H/V spectral ratios in OGF and found their repeated temporary drops. These drops seemed to be derived from local fluid activities according to a numerical calculation. Based on this finding, we examined a coherency between the H/V spectral ratios and fluid activities in OGF and found a significance. In conclusion, monitoring H/V spectral ratios can enable us to grasp fluid activities that sometimes could lead to a relatively large seismic event.


2019 ◽  
Vol 1 (2) ◽  
pp. 41
Author(s):  
Triana Triana ◽  
Tony Yulianto ◽  
Udi Harmoko ◽  
Iqbal Takodama

Magnetotelluric data has been carried out at the "WS" geothermal field to analyze the resistivity model resulting from 2D inversion of magnetotelluric data in TE, TM and TE-TM modes. Base on the three models produced, the mode is determined to produce the most representative model to assist in the interpretation of the "WS" geothermal system. There is a step of modes separation, namely TE (Tranverse Electric) and TM (Transverse Magnetic) modes in processing MT data. Each mode produces a 2D model with different conductivity properties. The analysis results of the three modes explain that TE mode is dominated by low resistivity with a range of values of 10-35 Ωm and medium resistivity with a value range of 35-250 Ωm and a vertical resistivity contrast. The TM mode describes the high resistivity in the Southwest and the center of the track with a value of more than 470 sehinggam resulting in lateral resistivity contrast. While the TE-TM mode produces a model that is not much different from TM mode, only the distribution of the resistivity value is a combination with TE mode. This mode describes the distribution of resistivity both vertically and laterally. Based on the analysis of the three modes, it can be concluded that the TE-TM mode is the mode that produces the most representative model. Interpretation model shows that from the TE-TM mode we have a low resistivity distribution (10-35 Ωm) represent a cap rock zone, reservoir rock with a medium resistivity distribution (35-380 Ωm), resistive zone with a high resistivity distribution (more than 380 Ωm), and the existence of the three of faults structures ro be a controller system of the "WS" geothermal.


2019 ◽  
Vol 220 (1) ◽  
pp. 541-567 ◽  
Author(s):  
Benjamin Lee ◽  
Martyn Unsworth ◽  
Knútur Árnason ◽  
Darcy Cordell

SUMMARY Krafla is an active volcanic field and a high-temperature geothermal system in northeast Iceland. As part of a program to produce more energy from higher temperature wells, the IDDP-1 well was drilled in 2009 to reach supercritical fluid conditions below the Krafla geothermal field. However, drilling ended prematurely when the well unexpectedly encountered rhyolite magma at a depth of 2.1 km. In this paper we re-examine the magnetotelluric (MT) data that were used to model the electrical resistivity structure at Krafla. We present a new 3-D resistivity model that differs from previous inversions due to (1) using the full impedance tensor data and (2) a finely discretized mesh with horizontal cell dimensions of 100 m by 100 m. We obtained similar resistivity models from using two different prior models: a uniform half-space, and a previously published 1-D resistivity model. Our model contains a near-surface resistive layer of unaltered basalt and a low resistivity layer of hydrothermal alteration (C1). A resistive region (R1) at 1 to 2 km depth corresponds to chlorite-epidote alteration minerals that are stable at temperatures of about 220 to 500 °C. A low resistivity feature (C2) coincides with the Hveragil fault system, a zone of increased permeability allowing interaction of aquifer fluids with magmatic fluids and gases. Our model contains a large, low resistivity zone (C3) below the northern half of the Krafla volcanic field that domes upward to a depth of about 1.6 km b.s.l. C3 is partially coincident with reported low S-wave velocity zones which could be due to partial melt or aqueous fluids. The low resistivity could also be attributed to dehydration and decomposition of chlorite and epidote that occurs above 500 °C. As opposed to previously published resistivity models, our resistivity model shows that IDDP-1 encountered rhyolite magma near the upper edge of C3, where it intersects C2. In order to assess the sensitivity of the MT data to melt at the bottom of IDDP-1, we added hypothetical magma bodies with resistivities of 0.1 to 30 Ωm to our resistivity model and compared the synthetic MT data to the original inversion response. We used two methods to compare the MT data fit: (1) the change in r.m.s. misfit and (2) an asymptotic p-value obtained from the Kolmogorov–Smirnov (K–S) statistical test on the two sets of data residuals. We determined that the MT data can only detect sills that are unrealistically large (2.25 km3) with very low resistivities (0.1 or 0.3 Ωm). Smaller magma bodies (0.125 and 1 km3) were not detected; thus the MT data are not sensitive to small rhyolite magma bodies near the bottom of IDDP-1. Our tests gave similar results when evaluating the changes in r.m.s. misfit and the K–S test p-values, but the K–S test is a more objective method than appraising a relative change in r.m.s. misfit. Our resistivity model and resolution tests are consistent with the idea of rhyolite melt forming by re-melting of hydrothermally altered basalt on the edges of a deeper magma body.


2018 ◽  
Vol 70 (1) ◽  
Author(s):  
Kyosuke Okamoto ◽  
Li Yi ◽  
Hiroshi Asanuma ◽  
Takashi Okabe ◽  
Yasuyuki Abe ◽  
...  

2020 ◽  
Vol 2 (2) ◽  
pp. 85-89
Author(s):  
Nabil Bawahab ◽  
Udi Harmoko ◽  
Tony Yulianto ◽  
Irvan Ramadhan

Magnetotelluric research in the “N” geothermal field has been carried out to see the subsurface detail in the “N” geothermal field. 2D inversion model is generated by secondary data from magnetotelluric data collection in the form of time series data to become 2D models. Magnetotellurics method is used to identify geothermal system components, especially identifying layers with low resistivity values (2 Ω.m - 10 Ω.m) or also called as the cap rock which is seen with a very contrasting color difference compared to the surrounding layers. There are manifestations on the “N” geothermal field which reinforce the assumption that there is a geothermal system in this area. This research begins by processing time series data to become apparent resistivity and phase data. Time series data processing in this study uses several processing methods to produce better apparent resistivity and phase data. The final result of this study is a 2D model that illustrates the contour of the resistivity value of rocks laterally or vertically. 2D model interpretation in this study identified the cap rock layer with low resistivity distribution (2 Ω.m - 10 Ω.m), the medium resistivity zone identified as the reservoir layer (11 Ω.m - 70 Ω.m), and the resistive zone which has high resistivity value (more than 70 Ω.m).


2021 ◽  
Author(s):  
◽  
Gabriel Matson

<p>The high-temperature, fluid-dominated Ngatamariki geothermal field is located in the central Taupo Volcanic Zone, North Island, New Zealand, and is used to generate electricity via an 82 MW power plant. Injection wells have been in operation since June 2012. During June and July 2012, injection well NM8 was injected with with cold water in order to improve reservoir permeability. Geothermal stimulation and production may trigger microearthquakes by fluid flow through the reservoir. Close clustering of microseismic events’ hypocentres relative to the source-receiver distance results in many events having similar waveforms. We capitalize on this relationship by using a matched-filter detection method in which high-quality seismograms corresponding to a well-recorded earthquake (“templates”) are cross-correlated against continuous data to reveal additional earthquakes with similar characteristics. Clustering of the detections’ hypocenters also implies that small variations in travel times between two events corresponds to small differences in hypocentral locations, which is the foundation of the double-difference relocation method.  Using an 11 station seismic network, we detect 863 events via cross-correlation of 110 matched-filter templates during the two months stimulation testing. We locate each of these detections using a double-difference relocation method by which events are relocated based on relative travel times. The locatable seismicity delineates: a northern Ngatamariki cluster, a southern Ngatamariki cluster, and a cluster to the south, at the neighboring Rotokawa field. Seismicity in the northern Ngatamariki cluster (522 events) is of greatest interest for this project due to its proximity to well NM8 and temporal signature relative to injection. The seismicity cluster centers around well NM8 at a depth of 2.1 km below sea level. Events in this cluster extend to up to 2.5 km from the injection well. An increase in seismicity near NM8 lags behind the onset of injection by 4–8 days. In contrast, a seismicity-rate decrease coincides with injection shut-in without any time lag. Local magnitudes in this cluster span the range −0.09 ≤ Ml ≤ 1.66 with a completeness magnitude of 0.25. Seismicity within 200 m of NM8 is induced by thermal stresses caused by the difference in temperature between the injectate and the reservoir. Seismicity further than 200 m, but still within this cluster, from NM8 is induced via pore fluid pressure increases from the injected fluid. The coupled mechanism acts on two different length scales and is known as a thermoporoelastic mechanism. The matched-filter detection of microseismic events allows interpretation of extent of injection well stimulation and the relationship between injection and seismicity.</p>


2019 ◽  
Author(s):  
Kyosuke Okamoto ◽  
Hiroshi Asanuma ◽  
Takashi Okabe ◽  
Yasuyuki Abe ◽  
Masatoshi Tsuzuki

2021 ◽  
Author(s):  
◽  
Gabriel Matson

<p>The high-temperature, fluid-dominated Ngatamariki geothermal field is located in the central Taupo Volcanic Zone, North Island, New Zealand, and is used to generate electricity via an 82 MW power plant. Injection wells have been in operation since June 2012. During June and July 2012, injection well NM8 was injected with with cold water in order to improve reservoir permeability. Geothermal stimulation and production may trigger microearthquakes by fluid flow through the reservoir. Close clustering of microseismic events’ hypocentres relative to the source-receiver distance results in many events having similar waveforms. We capitalize on this relationship by using a matched-filter detection method in which high-quality seismograms corresponding to a well-recorded earthquake (“templates”) are cross-correlated against continuous data to reveal additional earthquakes with similar characteristics. Clustering of the detections’ hypocenters also implies that small variations in travel times between two events corresponds to small differences in hypocentral locations, which is the foundation of the double-difference relocation method.  Using an 11 station seismic network, we detect 863 events via cross-correlation of 110 matched-filter templates during the two months stimulation testing. We locate each of these detections using a double-difference relocation method by which events are relocated based on relative travel times. The locatable seismicity delineates: a northern Ngatamariki cluster, a southern Ngatamariki cluster, and a cluster to the south, at the neighboring Rotokawa field. Seismicity in the northern Ngatamariki cluster (522 events) is of greatest interest for this project due to its proximity to well NM8 and temporal signature relative to injection. The seismicity cluster centers around well NM8 at a depth of 2.1 km below sea level. Events in this cluster extend to up to 2.5 km from the injection well. An increase in seismicity near NM8 lags behind the onset of injection by 4–8 days. In contrast, a seismicity-rate decrease coincides with injection shut-in without any time lag. Local magnitudes in this cluster span the range −0.09 ≤ Ml ≤ 1.66 with a completeness magnitude of 0.25. Seismicity within 200 m of NM8 is induced by thermal stresses caused by the difference in temperature between the injectate and the reservoir. Seismicity further than 200 m, but still within this cluster, from NM8 is induced via pore fluid pressure increases from the injected fluid. The coupled mechanism acts on two different length scales and is known as a thermoporoelastic mechanism. The matched-filter detection of microseismic events allows interpretation of extent of injection well stimulation and the relationship between injection and seismicity.</p>


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