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Abstract Fractures control fluid flow, mass transport, and heat transfer in a geothermal reservoir. This makes accurate characterization of fracture networks a prerequisite for optimal design and control of a reservoir's exploitation. We develop a deep‐learning procedure to identify fracture locations via interpretation of temporally and spatially continuous downhole temperature measurements. A long short‐term memory fully convolutional network (LSTM‐FCN) is used both to capture long‐term dependencies in sequential temperature data and to distill local features around fractures. A wellbore and fractured‐reservoir thermal model is established to generate temperature data for network training. The trained LSTM‐FCN exhibits a unique ability to detect multiple fractures intersecting a borehole. We use the LSTM‐FCN algorithm to evaluate the effectiveness of different‐stage wellbore temperature measurements on fracture detection in a complex fractured system. Our experiments reveal that the use of various‐stage temperature information as an input feature set improves the robustness of fracture detection to noise interference. This study indicates the practical feasibility of obtaining accurate fracture‐network reconstructions from temperature signals, at reasonable computational cost.
We present the largest M31 near-infrared (F110W (close to J band), F160W (H band)) Cepheid sample so far. The sample consists of 371 Cepheids with photometry obtained from the Hubble Space Telescope PHAT program. The sample of 319 fundamental mode Cepheids, 16 first overtone Cepheids, and 36 type II Cepheids was identified using the median absolute deviation outlier rejection method we develop here. This method does not rely on priors and allows us to obtain this clean Cepheid sample without rejecting a large fraction of Cepheids. The obtained period-luminosity relations (PLRs) have a very small dispersion, i.e., 0.155 mag in F160W, despite using random phased observations. This remarkably small dispersion allows us to determine that the PLRs are significantly better described by a broken slope at 10 days than a linear slope. The use of our sample as an anchor to determine the Hubble constant gives a 3.2% larger Hubble constant compared to the Riess et al. sample.
Atomic transition probability measurements for 371 Ni I lines in the UV through near-IR are reported. Branching fractions from data recorded using a Fourier transform spectrometer and a new echelle spectrograph are combined with published radiative lifetimes to determine these transition probabilities. Generally good agreement is found in comparisons to previously reported Ni I transition probability measurements. Use of the new echelle spectrograph, independent radiometric calibration methods, and independent data analysis routines enable a reduction of systematic errors and overall improvement in transition probability uncertainty over previous measurements. The new Ni I data are applied to high-resolution visible and UV spectra of the Sun and metal-poor star HD 84937 to derive new, more accurate Ni abundances. Lines covering a wide range of wavelength and excitation potential are used to search for non-LTE effects.
We study a model of inflation with terms quadratic and logarithmic in the Ricci scalar, where the gravitational action is f(R)=R+α R{sup 2}+β R{sup 2} ln R. These terms are expected to arise from one loop corrections involving matter fields in curved space-time. The spectral index n{sub s} and the tensor to scalar ratio yield 4 × 10{sup -4}∼< r∼<0.03 and 0.94∼< n{sub s} ∼< 0.99. i.e. r is an order of magnitude bigger or smaller than the original Starobinsky model which predicted r∼ 10{sup -3}. Further enhancement of r gives a scale invariant n{sub s}∼ 1 or higher. Other inflationary observables are d n{sub s}/dln k ∼> -5.2 × 10{sup -4}, μ ∼< 2.1 × 10{sup -8} , y ∼< 2.6 × 10{sup -9}. Despite the enhancement in r, if the recent BICEP2 measurement stands, this model is disfavoured.
Abstract We describe an algorithm based on a logarithmic barrier function, Newton’s method and linear conjugate gradients that seeks an approximate minimizer of a smooth function over the non-negative orthant. We develop a bound on the complexity of the approach, stated in terms of the required accuracy and the cost of a single gradient evaluation of the objective function and/or a matrix-vector multiplication involving the Hessian of the objective. The approach can be implemented without explicit calculation or storage of the Hessian.
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We investigate the high Q 2 (photon virtuality) limit of single-inclusive hadron production in deep inelastic scattering at small x , using the color glass condensate formalism at next-to-leading order. We focus on the Λ QCD 2 ≪ p h 2 ≪ Q 2 kinematic regime, where p h is the produced hadron transverse momentum, and extract the Sudakov double logarithms. We further argue that compatibility between the color glass condensate calculation and transverse momentum dependent distribution factorization at one-loop order can only be achieved if the small-x evolution is kinematically constrained. Published by the American Physical Society 2024
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In this report, we describe a data analysis tool developed for decoding and analyzing vehicle data obtained from a passenger vehicle’s onboard controller area network (CAN) bus. The tool developed in this paper provides a timeseries framework to perform domain-specific analysis at scale when interpreting data from a vehicle or a collection of vehicles in light of how to design intelligent vehicle applications. The tool, called Strym, exploits the CAN bus mechanism of modern vehicles to capture data using commercially available CAN-to-USB hardware Comma.ai Panda devices, managed through open-source software Libpanda. Strym permits the decoding of vendor-specific CAN messages in a vehicle-agnostic manner. Through this, a researcher can characterize data throughput, assess data quality, and perform analyses. Such analyses are useful in a number of research such as studying human driving behavior in mixed-autonomy, new driver models, rare-event detection, traffic flow estimation, and custom control of vehicles.
Purpose: In this study we will compare the ability of three QA methods (Delta4, MU-EPID, Dynalog QA) to detect specific errors. Methods: A Varian Novalis Tx with a HD120 MLC and aS1000 Electronic Portal Imaging Device (EPID) was used in our study. Multi-leaf collimator (MLC) errors, gantry angle and dose errors were introduced into 5 volumetric arc therapy (VMAT) plans. 3D dose distributions calculated with data from the EPID and Dynalog QA methods were compared with the planned dose distribution. The gamma passing percentages as well as percentage error of planning target volume (PTV) dose were used for passing determination. Baselines for gamma passing percentages and PTV dose were established by measuring the original plan 5 times consecutively. Standard passing thresholds as well as thresholds derived from receiver operator characteristic (ROC) analysis and 2 standard deviation (SD) criteria were used. Results: When applying the standard 95% pass rate at 3%/3mm gamma analysis 14, 21 and 8 of 30 errors were detected by the Delta4, MU-EPID and Dynalog QA methods respectively. Thresholds set at 2 SD from our base line measurements resulted in the detection of 18, 9 and 14 of 30 errors for the Delta4, MU-EPID and Dynalog QA methods respectively. When using D2 of the PTV as a metric the Dynalog QA detected 20 of 30 errors while the EPID method detected 14 of 30 errors. Using D98 of the PTV, Dynalog QA detected 13 of 30 while the EPID detected 3 of 30 errors. Conclusion: Although MU-EPID detected the most errors at the standard 95% cutoff it also produced the most false detections in the baseline data. The Dynalog QA was the most effective when the ROC adjusted passing threshold was used. D2 was more effective as a metric for detecting errors than D98.
Purpose: To present treatment statistics of a Varian Novalis Tx using more than 90,000 Varian Dynalog files collected over the past 2 years. Methods: Varian Dynalog files are recorded for every patient treated on our Varian Novalis Tx. The files are collected and analyzed daily to check interfraction agreement of treatment deliveries. This is accomplished by creating fluence maps from the data contained in the Dynalog files. From the Dynalog files we have also compiled statistics for treatment delivery times, MLC errors, gantry errors and collimator errors. Results: The mean treatment time for VMAT patients was 153 ± 86 seconds while the mean treatment time for step & shoot was 256 ± 149 seconds. Patient’s treatment times showed a variation of 0.4% over there treatment course for VMAT and 0.5% for step & shoot. The average field sizes were 40 cm2 and 26 cm2 for VMAT and step & shoot respectively. VMAT beams contained and average overall leaf travel of 34.17 meters and step & shoot beams averaged less than half of that at 15.93 meters. When comparing planned and delivered fluence maps generated using the Dynalog files VMAT plans showed an average gamma passing percentage of 99.85 ± 0.47. Step & shoot plans showed an average gamma passing percentage of 97.04 ± 0.04. 5.3% of beams contained an MLC error greater than 1 mm and 2.4% had an error greater than 2mm. The mean gantry speed for VMAT plans was 1.01 degrees/s with a maximum of 6.5 degrees/s. Conclusion: Varian Dynalog files are useful for monitoring machine performance treatment parameters. The Dynalog files have shown that the performance of the Novalis Tx is consistent over the course of a patients treatment with only slight variations in patient treatment times and a low rate of MLC errors.
The authors have designed a multi-purpose multi-channel data recording and transmission system for the laser strainmeters and the related geophysical and seismic equipment intended for service in operating mines.
An understanding of trap and fault seal quality is critical for assessing hydrocarbon prospectivity. To achieve this, modern analytical techniques leverage well data and conventional industry-standard 3D seismic data to evaluate the trap, and any faults displacing the reservoir and top seal intervals. Above all, geological interpretation provides the framework of trap and fault seal analyses, but can be hindered by the data resolution, quality and acquisition style of the conventional seismic data. Furthermore, limiting the analysis to only the petroleum system at depth may lead to erroneous perceptions because interpreting overburden features, such as shallow faults or gas chimneys, can provide valuable observations with respect to container performance, and can to help validate trap and fault seal predictions. Here, a supplement to conventional 3D data are high-resolution 3D seismic (HR3D) data, which provide detailed images of the overburden geology. This study utilizes an HR3D seismic volume in the San Luis Pass area of the Texas inner shelf, where shallow fault tips and a sizeable gas chimney are interpreted over an unsuccessful hydrocarbon prospect. Static post-drill fault seal and trap analyses suggest that the primary fault displacing the structural closure could have withheld columns of gas c. 100 m high, but disagree with our HR3D seismic interpretations and dry-well analyses. From our results, we hypothesize that tertiary gas migration through fault conduits reduced the hydrocarbon column in the prospective Early Miocene reservoir, and may have resulted from continued movement along the intersecting faults. Overall, this study reinforces the importance of understanding the overburden geology and geohistory of faulted prospects, and demonstrates the utility of pre-drill HR3D acquisition when conducting trap and fault seal analyses.