Classification of Land-Water Continuum Habitats Using Exclusively Airborne Topobathymetric Lidar Green Waveforms and Infrared Intensity Point Clouds

Coastal areas host highly valuable ecosystems that are increasingly exposed to the threats of global and local changes. Monitoring their evolution at a high temporal and spatial scale is therefore crucial and mostly possible through remote sensing. This article demonstrates the relevance of topobathymetric lidar data for coastal and estuarine habitat mapping by classifying bispectral data to produce 3D maps of 21 land and sea covers at very high resolution. Green lidar full waveforms are processed to retrieve tailored features corresponding to the signature of those habitats. These features, along with infrared intensities and elevations, are used as predictors for random forest classifications, and their respective contribution to the accuracy of the results is assessed. We find that green waveform features, infrared intensities, and elevations are complimentary and yield the best classification results when used in combination. With this configuration, a classification accuracy of 90.5% is achieved for the segmentation of our dual-wavelength lidar dataset. Eventually, we produce an original mapping of a coastal site under the form of a point cloud, paving the way for 3D classification and management of land and sea covers.

Localizing microseismic events on field data using a U-Net based convolutional neural network trained on synthetic data

Hydraulic fracturing plays an important role when it comes to the extraction of resources in unconventional reservoirs. The microseismic activity arising during hydraulic fracturing operations needs to be monitored to both improve productivity and to make decisions about mitigation measures. Recently, deep learning methods have been investigated to localize earthquakes given field-data waveforms as input. For optimal results, these methods require large field data sets that cover the entire region of interest. In practice, such data sets are often scarce. To overcome this shortcoming, we propose initially to use a (large) synthetic data set with full waveforms to train a U-Net that reconstructs the source location as a 3D Gaussian distribution. As field data set for our study we use data recorded during hydraulic fracturing operations in Texas. Synthetic waveforms were modelled using a velocity model from the site that was also used for a conventional diffraction-stacking (DS) approach. To increase the U-Nets’ ability to localize seismic events, we augmented the synthetic data with different techniques, including the addition of field noise. We select the best performing U-Net using 22 events that have previously been identified to be confidently localized by DS and apply that U-Net to all 1245 events. We compare our predicted locations to DS and the DS locations refined by a relative location (DSRL) method. The U-Net based locations are better constrained in depth compared to DS and the mean hypocenter difference with respect to DSRL locations is 163 meters. This shows potential for the use of synthetic data to complement or replace field data for training. Furthermore, after training, the method returns the source locations in near real-time given the full waveforms, alleviating the need to pick arrival times.

Signal processing techniques for precise timing with novel gaseous detectors

The experimental requirements in current and near-future accelerators and experiments have stimulated intense interest in R&D of detectors with high precision timing capabilities, resulting in novel instrumentation. During the R&D phase, the timing information is usually extracted from the signal using the full waveform collected with fast oscilloscopes; this method produces a large amount of data and it becomes impractical when the detector has many channels. Towards practical applications, the data acquisition should be undertaken by dedicated front-end electronic units. The selected technology should retain the signal timing characteristics and consequently the timing resolution on the particle’s arrival time. We investigate the adequacy of the Leading-edge discrimination timing technique to achieve timing with a precision in the order of tens of picosecond with novel gaseous detectors. The method under investigation introduces a “time-walk” which impinges on the timing resolution. We mitigate the effect of time-walk using three different approaches; the first based on multiple Time-over-Threshold, the second based on multiple Charge-over-Threshold information and the third uses artificial Neural Network techniques. The results of this study prove the feasibility of the methods and their ability to achieve a timing resolution comparable to that obtained using the full waveforms.

Rupture Directivity in 3D Inferred From Acoustic Emissions Events in a Mine-Scale Hydraulic Fracturing Experiment

Rupture directivity, implying a predominant earthquake rupture propagation direction, is typically inferred upon the identification of 2D azimuthal patterns of seismic observations for weak to large earthquakes using surface-monitoring networks. However, the recent increase of 3D monitoring networks deployed in the shallow subsurface and underground laboratories toward the monitoring of microseismicity allows to extend the directivity analysis to 3D modeling, beyond the usual range of magnitudes. The high-quality full waveforms recorded for the largest, decimeter-scale acoustic emission (AE) events during a meter-scale hydraulic fracturing experiment in granites at ∼410 m depth allow us to resolve the apparent durations observed at each AE sensor to analyze 3D-directivity effects. Unilateral and (asymmetric) bilateral ruptures are then characterized by the introduction of a parameter κ, representing the angle between the directivity vector and the station vector. While the cloud of AE activity indicates the planes of the hydrofractures, the resolved directivity vectors show off-plane orientations, indicating that rupture planes of microfractures on a scale of centimeters have different geometries. Our results reveal a general alignment of the rupture directivity with the orientation of the minimum horizontal stress, implying that not only the slip direction but also the fracture growth produced by the fluid injections is controlled by the local stress conditions.

Experimental studies on the mechanism of seismoelectric logging while drilling with multipole source

Summary When a seismic wave propagates in a fluid-saturated porous medium, a relative movement forms between the solid and fluid and induces an electric current due to the electronic double layer. As a result, two kinds of seismoelectric coupling responses are generated in this procedure, i.e. the localized electric/magnetic field and interfacial electromagnetic wave field. One important potential application of these two seismoelectric conversions is used for measuring formation P and S waves in well logging. Considering that the strong collar wave seriously affects the velocity measurements of formation P and S waves in current acoustic logging while drilling (LWD), the seismoelectric logging while drilling method, which combines seismoelectric conversion and acoustic LWD technique, was suggested to be a novel method in oil and gas exploration. Because the collar wave can't induce any seismoelectric signal on the metal collar, since there is no double layer formed on a metal surface. In this paper, acoustic and seismoelectric LWD measurements are conducted in the laboratory. We build a scaled multipole acoustic LWD tool to conduct acoustic measurements in a water tank and a sandstone borehole model. We also build a multipole seismoelectric LWD tool and record the seismoelectric signals induced with the same acoustic source. Then we compare the recorded acoustic and seismoelectric signals by using the experimental data. The result indicates that the apparent velocities of seismoelectric signals are equal to the formation P and S wave velocities and the collar waves do not induce any visible electric signal in the full waveforms. We further analyze the mechanism of seismoelectric LWD by a quantitative comparison of the amplitudes between the inner collar wave and outer collar wave. The results show that the amplitude of outer collar wave decreases significantly when it radiates out of the tool, so that the seismoelectric signals induced by collar waves are too weak to be distinguished in the full waveforms of seismoelectric LWD measurements. Thus, the formation P and S wave velocities are detected accurately from the recorded seismoelectric LWD data. These results verify the feasibility of seismoelectric LWD method for measuring acoustic velocities of the borehole formation.

Acoustic fields for monopole logging while drilling with an eccentric collar

The acoustic problem of an eccentric drill collar in a fluid-filled borehole has been of interest in the field of acoustic logging while drilling (ALWD) in recent years. To reduce the effects of tool eccentricity on ALWD measurements, studies on acoustic responses under such conditions are essential. This study therefore has developed an analytical method to investigate borehole wavefields with an off-center monopole ALWD tool in both fast and slow formations. By evaluating the contributions of compressional and shear branch points, the effects of the tool eccentricity on individual formation primary and shear head waves were investigated. Results illustrate that tool eccentricity only affects the excitation properties, while it has almost no effect on the extracted velocities. The joint analysis of synthetic full waveforms and dispersion diagrams with varying eccentricity degrees indicates that multipole modes are excited when the tool is off-center, and their excitation amplitudes gradually increase with increasing eccentricity, especially in the direction of tool movement. Moreover, the dispersion analysis reveals that the two modes with intersections in the centered case are coupled when the tool becomes eccentric. In particular, the coupling performance between the Stoneley and flexural modes is the most prominent. Furthermore, the effects of tool eccentricity on the monopole acquisition method, i.e., the sum of waveforms received at four orthogonal azimuths, are evaluated. Results show that the above summation method can effectively reduce the effects of slight or moderate eccentricity. However, for large or extreme eccentricity, reducing or eliminating the effects of eccentricity on the Stoneley wave is a challenge for this method. Based on the above analyses, measurements may not be reliable for formation evaluation in the case of extreme eccentricity, especially for Stoneley wave applications.

Abstract 156: Capnographic Differences in Out-of-hospital Overdose-related, Respiratory, and Cardiac Arrests

Background: Little is known about the ventilatory aspects of overdose-related OHCA (OD-OHCA). We compared maximum ETCO2 (mETCO2; each patient’s highest CO2 level) and mean for each recorded minute of CPR in OD-OHCA to that of respiratory (R-OHCA) and cardiac (C-OHCA) arrests. Methods: Continuous CO2 data (Zoll E/X series monitors) were obtained from 3 Arizona EMS agencies. Cases had at least 3 min of recorded CO2 during CPR. Arrests were classified as OD-OHCA by EMS and/or hospital documentation. Any drug OD was included (e.g., opioids, mixed). C-OHCA and R-OHCA cases were randomly chosen for comparison. The groups were compared using Fisher’s exact test or Chi-squared for categorical and Kruskal-Wallis for continuous variables. Results: Included were 263 subjects (37 OD-OHCA, 157 C-OHCA and 69 R-OHCA; median age 61, 64% male, 1/10-12/18) with 10,271 min of data [median resuscitation interval 37 min (IQR 29, 47)]. Mean ETCO2 (SD): OD-OHCA [41 mmHg (24)]; R-OHCA [40 (23)], C-OHCA [30 (13); p<0.01]. Median mETCO2: OD-OHCA [57 mmHg (95CI: 50, 77)]; R-OHCA [61 (50, 73)], C-OHCA [48 (44, 50); p<0.001; Fig 1]. While mean ETCO2 and mETCO2 were similar for OD-OHCA and R-OHCA, they were both significantly higher than C-OHCA (p<0.01 for all comparisons). ETCO2 waveforms in OD-OHCA resembled the very high, full waveforms typical of R-OHCA while those in C-OHCA tended to be low and blunted. Conclusions: We believe this is the first report of continuous capnography during resuscitation of OD-OHCA. The mean ETCO2 and median of mETCO2 of OD-OHCA and R-OHCA imply similar physiology (hypoventilation and hypercapnia leading to arrest). Both etiologies had much higher ETCO2 values compared to C-OHCA, where low blood flow delivers minimal CO2 to the lungs and yields low, and morphologically different, waveforms. Future studies assessing OD arrest physiology and various approaches to resuscitation and pharmacological reversal are needed.