scholarly journals Multivariate statistical appraisal of regional susceptibility to induced seismicity: application to the Permian Basin, SW United States

2021 ◽  
Author(s):  
Stephen Hicks ◽  
Saskia Goes ◽  
Alexander Whittaker ◽  
Peter Stafford
Keyword(s):  
Induced Seismicity ◽  
Salt Water ◽  
Regional Scale ◽  
Physical Models ◽  
Poor Correlation ◽  
Test Bed ◽  
Permian Basin ◽  
Multivariate Statistical ◽  
Geological Factors ◽  
Triggering Process

Induced earthquake sequences are typically interpreted through causal triggering mechanisms. However, studies of causality rarely consider large regions and why some regions experiencing similar anthropogenic activities remain largely aseismic. Therefore, it can be difficult to forecast seismic hazard at a regional scale. In contrast, multivariate statistical methods allow us to find the combinations of factors that correlate best with seismicity, which can help form the basis of hypotheses that can be subsequently tested with physical models. Such a statistical approach is particularly important for large regions with newly-emergent seismicity comprising multiple distinct clusters and multi-faceted industrial operations. Recent induced seismicity in the Permian Basin provides an excellent test-bed for multivariate statistical analyses because the main causal industrial and geological factors driving earthquakes in the region remain highly debated. Here, we use logistic regression to retrospectively predict the spatial variation of seismicity across the western Permian Basin. We reproduce the broad distribution of seismicity using a combination of both industrial and geological factors. Our model shows that hydraulic fracturing and/or hydrocarbon production from the Wolfcamp Shale is the strongest predictor of seismicity, although the physical triggering process is unclear due to uncertain earthquake depths. We also find that the proximity to neotectonic faults west of the Delaware Basin is another important factor that contributes to induced seismicity. This higher tectonic stressing, together with a poor correlation between seismicity and large-volume deep salt-water disposal wells indicates a very different mechanism of induced seismicity compared to that in Oklahoma.

Combining static and dynamic environmental factors at various scales to predict shallow landsliding in South Tyrol, Italy – The Proslide project

2021 ◽  
Author(s):  
Robin Kohrs ◽  
 Lotte de Vugt ◽  
Thomas Zieher ◽  
Alice Crespi ◽  
Mattia Rossi ◽  
...  
Keyword(s):  
Regional Scale ◽  
Remote Sensing Data ◽  
Predisposing Factors ◽  
Physical Models ◽  
Data Driven ◽  
Catchment Scale ◽  
Heterogeneous Model ◽  
South Tyrol ◽  
Daily Precipitation Data ◽  
Spatio Temporal

<p>Shallow landslides in alpine environments can constitute a serious threat to the exposed elements. The spatio-temporal occurrence of such slope movements is controlled by a combination of predisposing factors (e.g. topography), preparatory factors (e.g. wet periods, snow melting) and landslide triggers (e.g. heavy precipitation events).  </p><p>For large study areas, landslide assessments frequently focus either on the static predisposing factors to estimate landslide susceptibility using data-driven procedures, or exclusively on the triggering events to derive empirical rainfall thresholds. For smaller areas, dynamic physical models can reasonably be parameterized to simultaneously account for static and dynamic landslide controls.  </p><p>The recently accepted Proslide project aims to develop and test methods with the potential to improve the predictability of landslides for the Italian province of South Tyrol. It is envisaged to account for a variety of innovative input data at multiple spatio-temporal scales. In this context, we seek to exploit remote sensing data for the spatio-temporal description of landslide controlling factors (e.g. precipitation RADAR; satellite soil moisture) and to develop models that allow an integration of heterogeneous model inputs using both, data-driven approaches (regional scale) and physically-based models (catchment scale). This contribution presents the core ideas and methodical framework behind the Proslide project and its very first results (e.g. relationships between landslide observations and gridded daily precipitation data at regional scale). </p>

Complex Shear-Wave Anisotropy from Induced Earthquakes in West Texas

2020 ◽  
Vol 110 (5) ◽  
pp. 2242-2251 ◽  
Author(s):  
Regan Robinson ◽  
Aibing Li ◽  
Alexandros Savvaidis ◽  
Hongru Hu
Keyword(s):  
Shear Wave ◽  
Induced Seismicity ◽  
High Rate ◽  
Normal Faults ◽  
Permian Basin ◽  
Induced Earthquakes ◽  
Large Delay ◽  
Delaware Basin ◽  
West Texas ◽  
Shallow Earthquakes

ABSTRACT We have analyzed shear-wave splitting (SWS) data from local earthquakes in the Permian basin in west Texas to understand crustal stress change and induced seismicity. Two SWS parameters, the fast polarization direction and the delay time, are computed using a semiautomatic algorithm. Most measurements are determined in the Delaware basin and the Snyder area. In both regions, SWS fast directions are mostly consistent with local SHmax at stations that are relatively far from the earthquake clusters. Varying fast directions at one station are related to different ray paths and are probably caused by heterogeneity. In the Snyder area, most northeast–southwest fast directions are from the events in the northern part of the cluster, whereas the northwest–southeast fast directions are mostly from the southern part. The northeast–southwest and northwest–southeast fast directions could be attributed to the northeast-trending normal faults and the northwest-trending strike-slip faults, respectively. SWS results in the Delaware basin have two unique features. First, most shallow earthquakes less than 4 km deep produce relatively large delay times. This observation implies that the upper crust of the Delaware basin is highly fractured, as indicated by the increasing number of induced earthquakes. Second, diverse fast directions are observed at the stations in the high-seismicity region, likely caused by the presence of multiple sets of cracks with different orientations. This situation is possible in the crust with high pore pressure, which is expected in the Delaware basin due to extensive wastewater injection and hydraulic fracturing. We propose that the diversity of SWS fast directions could be a typical phenomenon in regions with a high rate of induced seismicity.

scholarly journals NMR Metabolomics Applied on the Discrimination of Variables Influencing Tomato (Solanum lycopersicum)

Molecules ◽  
2020 ◽  
Vol 25 (16) ◽  
pp. 3738
Author(s):  
Ana Cristina Abreu ◽  
Ignacio Fernández
Keyword(s):  
Solanum Lycopersicum ◽  
Metabolic Networks ◽  
Cultural Practices ◽  
Salt Water ◽  
Added Value ◽  
Food Sector ◽  
Multivariate Statistical ◽  
Stage Of Development ◽  
Cultivation Techniques ◽  
Aroma Components

Tomato composition and nutritional value are attracting increasing attention and interest from both consumers and producers. The interest in enhancing fruits’ quality with respect to beneficious nutrients and flavor/aroma components is based not only in their economic added value but also in their implications involving organoleptic and healthy properties and has generated considerable research interest among nutraceutical and horticultural industries. The present article reviews up to March 2020 some of the most relevant studies based on the application of NMR coupled to multivariate statistical analysis that have addressed the investigation on tomato (Solanum lycopersicum). Specifically, the NMR untargeted technique in the agri-food sector can generate comprehensive data on metabolic networks and is paving the way towards the understanding of variables affecting tomato crops and composition such as origin, variety, salt-water irrigation, cultivation techniques, stage of development, among many others. Such knowledge is helpful to improve fruit quality through cultural practices that divert the metabolism towards the desired pathways and, probably more importantly, drives further efforts towards the differentiation of those crops developed under controlled and desired agronomical conditions.

scholarly journals Overview of Selected Multivariate Statistical Methods and Their Use in Phytopathological Research

2004 ◽  
Vol 94 (9) ◽  
pp. 1004-1006 ◽  
Author(s):  
S. Sanogo ◽  
X. B. Yang
Keyword(s):  
Host Plants ◽  
Regional Scale ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Site Specific ◽  
Several Variables ◽  
Pathogenic Variation ◽  
Site Variation ◽  
Disease Epidemics ◽  
Physical And Chemical

To disentangle the nature of a pathosystem or a component of the system such as disease epidemics for descriptive or predictive purposes, mensuration is conducted on several variables of the physical and chemical environment, pathogenic populations, and host plants. For instance, it may be desired to (i) distinguish pathogenic variation among several isolates of a pathogen based on disease severity; (ii) identify the most important variables that characterize the structure of an epidemic; and (iii) assess the potential of developing regional scale versus site-specific postmanagement schemes using weather and site variation. In all these cases, a simultaneous handling of several variables is required, and entails the use of multivariate statistics such as discriminant analysis, multivariate analysis of variance, correspondence analysis, and canonical correlation analysis. These tools have been used to varying degree in the phytopathological literature. A succinct overview of these tools is presented with cited examples.

Characteristics of induced seismicity during hydraulic stimulations

2020 ◽  
Author(s):  
Georg Dresen ◽  
Stephan Bentz ◽  
Grzegorz Kwiatek ◽  
Patricia Martínez-Garzón ◽  
Marco Bohnhoff
Keyword(s):  
Real Time ◽  
Seismic Moment ◽  
Induced Seismicity ◽  
Fluid Volume ◽  
Physical Models ◽  
Traffic Light ◽  
Induced Earthquakes ◽  
Induced Earthquake ◽  
Energy Pumping ◽  
Good Agreement

<p>Near-realtime seismic monitoring of fluid injection allowed control of induced earthquakes during the stimulation of a 6.1 km deep geothermal well near Helsinki, Finland. The stimulation was monitored in near-real time using a deep seismic borehole array and series of borehole stations. Earthquakes were processed within a few minutes and results informed a Traffic Light System (TLS). Using near-realtime information on induced-earthquake rates, locations, magnitudes, and evolution of seismic and hydraulic energy, pumping was either stopped or varied. This procedure avoided the nucleation of a project-stopping red alert at magnitude M2.1 induced earthquake, a limit set by the TLS and local authorities. Our recent studies show that the majority of EGS stimulation campaigns investigated reveal a clear linear relation between injected fluid volume, hydraulic energy and cumulative seismic moments suggesting extended time-spans during which induced seismicity evolution is pressure-controlled. For most projects studied, the observations are in good agreement with existing physical models that predict a relation between injected fluid volume and maximum seismic moment of induced events. Some EGS stimulations however reveal unbound increase in seismic moment suggesting that for these cases evolution of seismicity is mainly controlled by stress field, the size of tectonic faults and fault connectivity. Transition between the two states may occur at any time during injection, or not at all. Monitoring and traffic-light systems used during stimulations need to account for the possibility of unstable rupture propagation from the very beginning of injection by observing the entire seismicity evolution in near-real-time and at high resolution could possibly provide a successful physics-based approach in reducing seismic hazard from stimulation-induced seismicity in geothermal projects.</p>

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