Quasi-shear wave ray tracing by wavefront construction in 3-D, anisotropic media

Wavefront construction (WFC) methods provide robust tools for computing ray theoretical traveltimes and amplitudes for multivalued wavefields. They simulate a wavefront propagating through a model using a mesh that is refined adaptively to ensure accuracy as rays diverge during propagation. However, an implementation for quasi-shear (qS) waves in anisotropic media can be very difficult, since the two qS slowness surfaces and wavefronts often intersect at shear-wave singularities. This complicates the task of creating the initial wavefront meshes, as a particular wavefront will be the faster qS-wave in some directions, but slower in others. Analogous problems arise during interpolation as the wavefront propagates, when an existing mesh cell that crosses a singularity on the wavefront is subdivided. Particle motion vectors provide the key information for correctly generating and interpolating wavefront meshes, as they will normally change slowly along a wavefront. Our implementation tests particle motion vectors to ensure correct initialization and propagation of the mesh for the chosen wave type and to confirm that the vectors change gradually along the wavefront. With this approach, the method provides a robust and efficient algorithm for modeling shear-wave propagation in a 3-D, anisotropic medium. We have successfully tested the qS-wave WFC in transversely isotropic models that include line singularities and kiss singularities. Results from a VTI model with a strong vertical gradient in velocity also show the accuracy of the implementation. In addition, we demonstrate that the WFC method can model a wavefront with a triplication caused by intrinsic anisotropy and that its multivalued traveltimes are mapped accurately. Finally, qS-wave synthetic seismograms are validated against an independent, full-waveform solution.     

Analysis of longitudinal profiles along the eastern margin of the Qinghai-Tibetan Plateau

Resulting from the collision of the Eurasian and Indian plates, the Qinghai-Tibetan Plateau is commonly known as the ’roof of the world’. Collectively the Yarlung Tsangpo, Nu, Lancang, Yangtze, Yalong, and Yellow River basins drain the eastern margin of the plateau. In this paper, we utilize Shuttle Radar Topography Mission elevation data to examine morphometric and relief attributes of these basins to reveal insights into tectonic activity and rates of incision. A robust technique using Matlab is proposed to alleviate errors associated with SRTM data in the derivation of river longitudinal profiles. Convex longitudinal profiles are interpreted to be a product of uplift rates that exceed rates of channel incision along the entire margin of the Qinghai-Tibetan Plateau. Highest relief towards the south reflects extensive fluvial incision. High relief is also prominent along major active faults. Erosion patterns are related to distance from knickpoints. Highest rates of erosion and incision are evident towards the south, with decreasing values towards the north, suggesting a link between tectonic activity and erosion.     

Geomorphology and environmental management of the Yellow River source zone

Geologic,climatic and anthropogenic factors have fashioned the distinctive landscapes and ecosystems of the Yellow River source zone(Brierley and Huang2013;Figure1).Located at thenorth-east corner of the Qinghai-Tibetan Plateau(QTP),at elevations between 2500 and 4500m,     

Ray travel time and distance for the planar polytrope

Ray travel time and distance are determined for the planar polytrope using analytic techniques that are specialized to plane stratified media. It is found that an adiabatically stratified polytrope yields non-dispersed wave fields for a full circuit of a ray through a trapping region. Non-adiabacity, however, leads to dispersion, and a consequent loss of correlation with successive circuits of the trapping region. An acoustic waveguide with fixed boundaries and a similar waveguide containing an isothermal stratified medium are also examined to illustrate the approach and to highlight various aspects of the ray behavior.     

Need and opportunity for a North American caribou knowledge cooperative

The importance of migratory caribou ( Rangifer tarandus ) to northerners, the increasing pressure to extract non-living resources, and predicted global climate change have led researchers, managers and resource users alike to focus on how to improve our knowledge of this unique northern ungulate. Unprecedented threats to caribou sustainability, along with the increasingly acknowledged value of indigenous hunters'contribution to caribou research, pose the additional challenge to innovate research methods that accommodate differing cultural perspectives and facilitate communication among groups. This paper surveys the state of scientific knowledge of the eleven major northern mainland herds of North America. We recommend an approach to improve our working knowledge of barren-ground caribou in order to assess better future impacts. The transfer of knowledge gained from years of research and indigenous experience on many aspects of caribou ecology should be evaluated and, where applicable, transferred to herds with more modest databases. The establishment of a North American Caribou Monitoring and Assessment System, based on a synthesis of local knowledge and research-based science, is recommended as a tool for improved communication and collective learning.     

The international at-sea intercomparison of fCO2 systems during the R/V Meteor Cruise 36/1 in the North Atlantic Ocean

The ‘International Intercomparison Exercise of fCO₂ Systems’ was carried out in 1996 during the R/V Meteor Cruise 36/1 from Bermuda/UK to Gran Canaria/Spain. Nine groups from six countries (Australia, Denmark, France, Germany, Japan, USA) participated in this exercise, bringing together 15 participants with seven underway fugacity of carbon dioxide (fCO₂) systems, one discrete fCO₂ system, and two underway pH systems, as well as systems for discrete measurement of total alkalinity and total dissolved inorganic carbon. Here, we compare surface seawater fCO₂ measured synchronously by all participating instruments. A common infrastructure (seawater and calibration gas supply), different quality checks (performance of calibration procedures for CO₂, temperature measurements) and a common procedure for calculation of final fCO₂ were provided to reduce the largest possible amount of controllable sources of error. The results show that under such conditions underway measurements of the fCO₂ in surface seawater and overlying air can be made to a high degree of agreement (±1 μatm) with a variety of possible equilibrator and system designs. Also, discrete fCO₂ measurements can be made in good agreement (±3 μatm) with underway fCO₂ data sets. However, even well-designed systems, which are operated without any obvious sign of malfunction, can show significant differences of the order of 10 μatm. Based on our results, no “best choice” for the type of the equilibrator nor specifics on its dimensions and flow rates of seawater and air can be made in regard to the achievable accuracy of the fCO₂ system. Measurements of equilibrator temperature do not seem to be made with the required accuracy resulting in significant errors in fCO₂ results. Calculation of fCO₂ from high-quality total dissolved inorganic carbon (C_T) and total alkalinity (A_T) measurements does not yield results comparable in accuracy and precision to fCO₂ measurements.     

Convolutional neural networks for automated microseismic detection in downhole distributed acoustic sensing data and comparison to a surface geophone array

Distributed acoustic sensing is a growing technology that enables affordable downhole recording of strain wavefields from microseismic events with spatial sampling down to ∼1 m. Exploiting this high spatial information density motivates different detection approaches than typically used for downhole geophones. A new machine learning method using convolutional neural networks is described that operates on the full strain wavefield. The method is tested using data recorded in a horizontal observation well during hydraulic fracturing in the Eagle Ford Shale, Texas, and the results are compared to a surface geophone array that simultaneously recorded microseismic activity. The neural network was trained using synthetic microseismic events injected into real ambient noise, and it was applied to detect events in the remaining data. There were 535 detections found and no false positives. In general, the signal-to-noise ratio of events recorded by distributed acoustic sensing was lower than the surface array and 368 of 933 surface array events were found. Despite this, 167 new events were found in distributed acoustic sensing data that had no detected counterpart in the surface array. These differences can be attributed to the different detection threshold that depends on both magnitude and distance to the optical fibre. As distributed acoustic sensing data quality continues to improve, neural networks offer many advantages for automated, real-time microseismic event detection, including low computational cost, minimal data pre-processing, low false trigger rates and continuous performance improvement as more training data are acquired.