scholarly journals Website – Spatial database for reservoir-triggered seismicity in Brazil

2019 ◽  
Author(s):  
Eveline Sayão ◽  
George França ◽  
Maristela Holanda ◽  
Alexandro Gonçalves

Abstract. After confirming that impoundment of large reservoirs could cause earthquakes worldwide, studies on reservoir-triggered seismicity (RTS) have had a considerable scientific incentive. Most of the studies determined that the vertical load increase due to reservoir load, and the reduction of effective effort due to the increase in pore pressure, can modify the stress regime in the reservoir region, possibly triggering earthquakes. In addition, the RTS is conditioned by several factors such as pre-existing tectonic stresses, reservoir size/weight, area-specific geological and hydromechanical conditions, constructive interaction between the orientation of seismotectonic forces, and additional load caused by the reservoir. One of the major challenges for studying RTS is to identify and correlate the factors in the area of influence of the reservoir, capable of influencing the RTS process itself. To assist the research, it was created a spatial seismicity-triggered reservoir database (BDSDR) based on the specifications of the national spatial data infrastructure (INDE), for gathering data pertinent to the RTS study in the area of reservoirs. In this context, this work presents the procedures and results found in the data processing of seismotectonic factors (dam height, reservoir volume, geology, and seismicity level) and compared with the dams that triggered earthquakes and the Brazilian dam catalog, which was then updated from 26 to 30 cases. The results indicate that the occurrence of RTS increases significantly with dam height since dams less than 50 m high cause only 2 % of earthquakes while those higher than 100 m cause about 54 %. The reservoir volume also plays a role and it was estimated that RTS occurrence requires a limiting minimum value of 1 × 10−4 km3. There was no clear correlation between the geology and geological provinces with RTS. The delayed response time of the reservoirs represents 43 % of the total, that is, almost half of them have hydraulic behavior. The highest magnitude, 4.2, was observed for an event that occurred in a reservoir with a volume greater than 10−3 km3. As a practical result to assist the analysis by the general community, the web viewer RISBRA (Reservoir Induced Seismicity in Brazil) was developed to serve as an interactive platform for BDSDR data.

2020 ◽  
Vol 20 (7) ◽  
pp. 2001-2019 ◽  
Author(s):  
Eveline Sayão ◽  
George Sand França ◽  
Maristela Holanda ◽  
Alexandro Gonçalves

Abstract. After confirming that impoundment of large reservoirs could cause earthquakes, studies on reservoir-triggered seismicity (RTS) have had a considerable scientific incentive. Most of the studies determined that the vertical load increase due to reservoir load, and the reduction of effective force due to the increase in pore pressure, can modify the stress field in the reservoir region, possibly triggering earthquakes. In addition, the RTS is conditioned by several factors such as pre-existing tectonic stresses, reservoir height/weight, area-specific geological and hydromechanical conditions, constructive interaction between the orientation of seismotectonic forces, and additional load caused by the reservoir. One of the major challenges in studying RTS is to identify and correlate the factors in the area of influence of the reservoir, capable of influencing the RTS process itself. A spatial seismicity-triggered reservoir database was created to facilitate the research in this field, based on the specifications of the national spatial data infrastructure (INDE), and to assemble data pertinent to the RTS study in the area of reservoirs. In this context, this work presents the procedures and results found in the data processing of seismotectonic factors (dam height, reservoir capacity, lithology, and seismicity) and compared first to the dams that triggered earthquakes and secondly to the Brazilian dam list. The list has been updated with four more cases, making a total of 30 cases. The results indicate that the occurrence of RTS increases significantly with dam height since dams less than 50 m high cause only 2 % of earthquakes while those higher than 100 m cause about 54 %. The reservoir volume also plays a role, and it was estimated that RTS occurrence requires a limiting minimum value of 1×10-4 km3. There was no clear correlation between the geology and geological provinces with RTS. The delayed response time of the reservoirs represents 43 % of the total; that is, almost half of them have hydraulic behavior. The highest magnitude, 4.2, was observed at a reservoir with a volume greater than 10−3 km3. As a practical outcome, to assist the analysis by the general community, the web viewer RISBRA (Reservoir Induced Seismicity in Brazil) was developed to serve as an interactive platform for Reservoir-Triggered Seismicity Database (BDSDR) data.


2016 ◽  
Vol 910 (4) ◽  
pp. 18-25
Author(s):  
S.S. Dyshlyuk ◽  
◽  
O.N. Nikolaeva ◽  
L.A. Romashova ◽  
◽  
...  

2021 ◽  
pp. 026666692110484
Author(s):  
Asmat Ali ◽  
Muhammad Imran ◽  
Munazza Jabeen ◽  
Zahir Ali ◽  
Syed Amer Mahmood

Spatial data is one of the core components in all information retrieval processes for decision-making. Spatial data acquisition consumes enormous monetary resources and time. The Integrated Geospatial Information Framework (IGIF) provides a basis and guide for developing, integrating, strengthening, and maximizing geospatial information management and related resources in all countries. To this, governments all over the world are establishing national spatial data infrastructures (SDIs). However, such initiatives face a considerable amount of resistance as organizations often do not want to share their data assets. The present study investigates these barriers in the establishment of national SDI in Pakistan. The constraints studied through the IGIF pathways and past studies were adapted via a pilot study and conceptualized in a hypothesized model. We collected primary data via the administration of 520 questionnaire surveys to 280 public and private organizations. Partial least squares structural equation modeling (PLS-SEM) was applied to statistically confirm the conceptual model of the barriers to disseminating spatial data. The results indicate institutional barriers from the absence of national data policy, lack of specified roles of stakeholders, poor inter-organizational coordination, missing data-sharing policy, and weak organizational partnerships, with coefficients 0.26, 1.555, 1.305, 8.288, and 0.136, respectively, at the p < 0.001 significance level. The PLS-SEM R2 0.65 indicates a good explanatory power of the model. The methodology developed in the present study will allow devising more sustainable policies for spatial data management and dissemination in Pakistan and beyond.


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