Azimuth Data Research Articles

Assessing Photo-Voltaic Potential in Urban Environments: A Comparative Study between Aerial Photogrammetry and LiDAR Technologies

Abstract. Urban development and population growth have significantly increased energy demands, predominantly met by non-renewable resources, negatively impacting nature and climate. Consequently, there has been a global shift towards renewable energy sources, with solar energy being widely adopted. Photovoltaic (PV) potential measures the usable electricity from solar energy using PV technology. With conventional methods, estimating PV potential involves converting 3D point cloud data to 2.5D elevation models, which can affect the accuracy of the estimation. A research gap exists in using adequate 3D point cloud datasets for PV potential estimation considering roof surface area and the surface normal vectors. This study compares aerial photogrammetry and aerial LiDAR point clouds for PV potential estimation against the DSM-based approach. Accurate PV potential estimation must consider solar incidence, roof area, azimuth, tilt angles, and PV efficiency. Traditional 2.5D methods often overlook crucial azimuth and tilt data, limiting the accuracy of the PV estimation. Converting 3D data to 2.5D may result in information loss, while 3D analyses offer higher accuracy. To investigate the mentioned gaps, this research aims to evaluate the capabilities of photogrammetry and LiDAR for urban PV potential estimation, highlighting their feasibility and accuracy over 2.5D methods.

Prestack reservoir prediction method in ray parameter domain based on wide azimuth ocean bottom node seismic data

AbstractWide azimuth seismic data play an important role in deep reservoir prediction. According to the Paleogene clastic rock reservoir prediction, the high‐density and wide azimuth 3D seismic data acquisition of ocean bottom nodes was first carried out in a Chinese offshore oilfield in 2019. After high precision amplitude‐preserving processing, we obtained the high‐quality wide azimuth gathers. However, the research on anisotropy and reservoir prediction using wide azimuth seismic data mainly focuses on carbonate and bedrock intervals, which is not suitable for clastic rock reservoir prediction. Therefore, this paper innovatively proposes a clastic rock reservoir prediction method, which studies prestack reservoir prediction in the ray parameter domain based on wide azimuth ocean bottom node seismic data. Based on the azimuth gathers, we can obtain elastic parameters through prestack amplitude versus offset inversion, which is used to characterize the reservoir, so it is significant to obtain high precision elastic parameters in order to get highly reliable reservoir prediction results. In this paper, we develop an amplitude versus offset inversion method based on the Bayesian theory in ray parameter domain, the output of which is density, P‐wave impedance and Vp/Vs. These elastic parameters have high precision, and density data are valuable input for reservoir characterization because they are sensitive to the lithology of clastic rock reservoir at different orientations. In ray parameter domain inversion, the ray path of seismic wave propagation is considered polyline, which is more consistent with the actual situation; thus, extracted amplitudes of P gathers used in inversion are more accurate. In addition, the reflection coefficient formula in ray parameter domain has higher precision when the incident angle is large. The inversion based on the Bayesian theory can improve the stability of the inversion. Test on the actual data shows that the result of ray parameter domain inversion with a Bayesian scheme is more accurate, stable and reliable. Based on the above high precision density inversion results, an innovative wide azimuth data reservoir prediction technology based on elliptical short‐axis fitting was proposed. The actual prediction of the deep reservoir in the Bohai oilfield shows that sand thickness fitting prediction results in the short axis can best match the actual drilling sandstone thickness. The coincidence rate is 86% and the short‐axis fitting results are more in agreement with geological laws. Theoretical research and practical applications have shown that this method is feasible and effective, with high prediction accuracy, computational efficiency and strong application value.

Facies variability and depositional cyclicity in central Northern Switzerland: insights from new Opalinus Clay drill cores

The Opalinus Clay, a silty to sandy claystone formation, Early to Middle Jurassic (Toarcian and Aalenian) in age, has been selected as the host rock for deep subsurface disposal of radioactive waste in Switzerland. Over the past thirty years, numerous geotechnical, mineralogical, and sedimentological studies have been conducted on the Opalinus Clay within the framework of the Nagra (National Cooperative for the Disposal of Radioactive Waste) deep drilling campaigns and the Mont Terri Project, an international research program dedicated to the study of claystone. The present study aims to unravel the variability of the lateral and vertical facies of the Opalinus Clay in central Northern Switzerland and to place this variability in a regional and basinal context. Analyses of new cores drilled in central Northern Switzerland, including petrographic, mineralogical (X-ray diffraction, multi-mineral interpretation), geochemical (X-ray fluorescence), statistical (non-metric multidimensional scaling analysis), and bedding dip and azimuth data, shed new light on the depositional facies and the spatial and temporal variability of the Opalinus Clay. Petrographic descriptions encompass nine new drill cores using a revised subfacies/facies classification scheme based on texture (colour, grain size, bedding) and composition (mineralogy). Particularly, one new subfacies (SF6) is described and interpreted as mass-wasting deposits. The drill cores are correlated laterally using specific marker horizons. This correlation is achieved by combining thorough facies investigations with lithostratigraphy, biostratigraphy, and chemostratigraphy. Six to seven small coarsening-upward cycles and two long-term coarsening-upward sequences can be interpreted as regressive trends. The observed trends are influenced by the interplay between sediment supply, eustatic sea level change, synsedimentary subsidence, but also the palaeogeographic configuration in an epicontinental sea, provenance and delivery of sediments, current dynamics and climate change. Finally, combined results show that the current dynamics in the Opalinus Clay has been underestimated until now and new depositional models, including the occurrence of drift deposits, are discussed.

Research on Aircraft Direction Finding Based on Antenna Directionality Parameter Identification

Radar direction finding is an essential cooperative monitoring method for aircraft, and the directional parameters of the direction-finding antenna determine the accuracy of direction finding. A modified amplitude comparison direction finding model is proposed based on the traditional principle of adjacent amplitude comparison direction finding and the error of amplitude comparison direction finding. Based on the modified amplitude comparison direction finding model, an error correction genetic simulated annealing (COR-GSA) algorithm is proposed to identify unknown directional antenna directionality parameters by determining the antenna directionality parameters that need to be identified. Identification experiments were conducted using a self-designed dual channel DF receiver, and 1000 sets of aircraft real azimuth data were used for verification. The results showed that using the COR-GSA algorithm to identify antenna directional parameters had the highest DF accuracy. Finally, the identified antenna directionality parameters were used to track the aircraft’s azimuth, and the tracking error was reduced by 18.3% compared to the tracking error without azimuth correction.

Human Multi-Activities Classification Using mmWave Radar: Feature Fusion in Time-Domain and PCANet.

This study introduces an innovative approach by incorporating statistical offset features, range profiles, time-frequency analyses, and azimuth-range-time characteristics to effectively identify various human daily activities. Our technique utilizes nine feature vectors consisting of six statistical offset features and three principal component analysis network (PCANet) fusion attributes. These statistical offset features are derived from combined elevation and azimuth data, considering their spatial angle relationships. The fusion attributes are generated through concurrent 1D networks using CNN-BiLSTM. The process begins with the temporal fusion of 3D range-azimuth-time data, followed by PCANet integration. Subsequently, a conventional classification model is employed to categorize a range of actions. Our methodology was tested with 21,000 samples across fourteen categories of human daily activities, demonstrating the effectiveness of our proposed solution. The experimental outcomes highlight the superior robustness of our method, particularly when using the Margenau-Hill Spectrogram for time-frequency analysis. When employing a random forest classifier, our approach outperformed other classifiers in terms of classification efficacy, achieving an average sensitivity, precision, F1, specificity, and accuracy of 98.25%, 98.25%, 98.25%, 99.87%, and 99.75%, respectively.

Automated high-precision alignment of geologic maps with well orientation

The 3D reflection seismic interpretation entails the creation of structure maps of subsurface horizons across extensive areas, often spanning tens of thousands of square kilometers within sedimentary basins. To be correlated with well measurements, maps made from 3D reflection seismic are routinely assigned the correct depth at well control points. However, integrating orientation information measured from wells remains a challenge due to the absence of upscaling guidelines. We address the scale-dependent nature of geologic structure and well orientation information in subsurface mapping, particularly focusing on integrating kilometer-scale seismic interpretation with centimeter-scale well-measured dip and azimuth data. Our pioneering methodology streamlines this integration process through three essential steps: first, transforming well dip and azimuth into a gradient representation; second, smoothly extending gradient differences between the map and well within a user-defined radius of influence; and third, constructing an updated horizon map by bicubic spline interpolation to ensure automated and high-precision alignment. In addition, a structure-oriented interpolation technique is introduced to preserve faults and local structures during orientation correction. Application of the methodology to a 3D reflection seismic horizon demonstrates its effectiveness in automating the complex task of tying subsurface maps to well orientation information. This not only reduces the need for manual interventions but also introduces a new perspective on subsurface mapping. It provides a robust framework that enhances the accuracy and reliability of geologic interpretation, offering significant advancements beyond previous efforts in the literature.

Automated pipeline processing X-ray diffraction data from dynamic compression experiments on the Extreme Conditions Beamline of PETRAIII.

Presented and discussed here is the implementation of a software solution that provides prompt X-ray diffraction data analysis during fast dynamic compression experiments conducted within the dynamic diamond anvil cell technique. It includes efficient data collection, streaming of data and metadata to a high-performance cluster (HPC), fast azimuthal data integration on the cluster, and tools for controlling the data processing steps and visualizing the data using the DIOPTAS software package. This data processing pipeline is invaluable for a great number of studies. The potential of the pipeline is illustrated with two examples of data collected on ammonia-water mixtures and multiphase mineral assemblies under high pressure. The pipeline is designed to be generic in nature and could be readily adapted to provide rapid feedback for many other X-ray diffraction techniques, e.g. large-volume press studies, in situ stress/strain studies, phase transformation studies, chemical reactions studied with high-resolution diffraction etc.

A Data Compression Method for Wellbore Stability Monitoring Based on Deep Autoencoder.

The compression method for wellbore trajectory data is crucial for monitoring wellbore stability. However, classical methods like methods based on Huffman coding, compressed sensing, and Differential Pulse Code Modulation (DPCM) suffer from low real-time performance, low compression ratios, and large errors between the reconstructed data and the source data. To address these issues, a new compression method is proposed, leveraging a deep autoencoder for the first time to significantly improve the compression ratio. Additionally, the method reduces error by compressing and transmitting residual data from the feature extraction process using quantization coding and Huffman coding. Furthermore, a mean filter based on the optimal standard deviation threshold is applied to further minimize error. Experimental results show that the proposed method achieves an average compression ratio of 4.05 for inclination and azimuth data; compared to the DPCM method, it is improved by 118.54%. Meanwhile, the average mean square error of the proposed method is 76.88, which is decreased by 82.46% when compared to the DPCM method. Ablation studies confirm the effectiveness of the proposed improvements. These findings highlight the efficacy of the proposed method in enhancing wellbore stability monitoring performance.

A Comprehensive Investigation of the Relationship between Fractures and Oil Production in a Giant Fractured Carbonate Field

This study examines the connections between various fracture indicators and production data with an example from one of the giant fields in the Middle East producing complex fractured carbonate lithologies. The field under study hosts two reservoirs with a long development and production history, including carbonates from the Asmari and Bangestan Formations. A fracture intensity map was generated based on the interpretation of image logs from 28 wells drilled within the field. Mud loss data were collected and mapped based on the geostatistical Gaussian Random Function Simulation (GRFS) algorithm. Maximum curvature maps were generated based on Asmari structural surface maps. Comparing the results shows a good agreement between the curvature map, fault distribution model, mud loss map, fracture intensity map, and productivity index. The results of image log interpretations led to the identification of four classes of open fractures, including major open fractures, medium open fractures, minor open fractures, and hairline fractures. Using the azimuth and dip data of the four fracture sets mentioned above, the fracture intensity log was generated as a continuous log for each well with available image log data. For this purpose, the fracture intensity log and a continuous fracture network (CFN) model were generated. The continuous fracture network model was used to generate a 3D discrete fracture network (DFN) for the Asmari Formation. Finally, a 3D upscaled model of fracture dip and azimuth, fracture porosity, fracture permeability, fracture length, fracture aperture, and the sigma parameter (the connectivity index between matrix and fracture) were obtained. The results of this study can illuminate the modeling of intricate reservoirs and the associated production challenges, providing insights not only during the initial production phase but also in the application of advanced oil recovery methods, such as thermal recovery.

In situ stress prediction method for decoupled overburden pressure under tectonic constraints

Abstract The prediction of in situ stress based on azimuthal seismic data has extensive use in horizon crushability evaluation. Nonetheless, existing in situ stress seismic prediction models do not consider overburden pressure and tectonic strain, which limit the prediction accuracy. To this end, we propose a decoupled overburden pressure in situ stress prediction method under tectonic constraints. The key to this method is to consider that the overburden pressure could act on the rock skeleton and pore fluid, i.e. generating effective pressure and pore pressure; the pore pressure can be estimated using Eaton's method, and then the effective stress can be obtained. The relationship between tectonic strain and effective pressure is constructed based on Hooke's law, where tectonic strain can be calculated from curvature attributes extracted from seismic data. Introducing pore pressure and deriving a model for calculating the maximum and minimum horizontal stresses and the difference in horizontal stress ratio for orthotropic media (OA). When the Thomson anisotropy parameters and the pore pressure are neglected, the proposed model can be degraded to a conventional horizontal transverse isotropy medium in situ stress prediction model, which proves the validity of the model. The results of sensitivity analysis experiments affirm the need to decouple overburden pressure and account for tectonic strain when predicting in situ stress reasonably. Finally, single-well and azimuthal seismic prediction were carried out by using the a priori information from well logging and seismic data.

Anisotropy Parameters Estimation in Stress-Induced Orthorhombic Reservoirs Based on Step-Wise Bayesian Inversion of Azimuthal Seismic Data

Anisotropy Parameters Estimation in Stress-Induced Orthorhombic Reservoirs Based on Step-Wise Bayesian Inversion of Azimuthal Seismic Data

A Novel Target Detection Method Based on Multi-Parameter Space for Mobile Passive Multistatic Radar

Deploying Passive Multistatic Radar (PMR) on mobile platforms provides covert and cost-effective monitoring over a large area, offering certain advantages in countermeasure. However, mobile PMR faces significant challenges, such as Doppler distortion and phase deviations. A multi-parameter space target detection method is proposed for mobile PMR to achieve target detection in three-dimensional environments. By estimating the Doppler Frequency Rate (DFR), applying bistatic range phase compensation, and implementing azimuth time integration, frame division, and data fusion, the detection accuracy and the Signal-to-Noise Ratio (SNR) are improved. Simulation results indicate that the proposed method significantly enhances the SNR and produces accurate detection results, demonstrating its efficacy.

System Design and Echo Preprocessing of Spaceborne Squinted Two-Dimensional Beam Scanning Synthetic Aperture Radar.

Conventional squinted sliding spotlight synthetic aperture radar (SAR) imaging suffers from substantial swath width reduction and complex processing requirements due to the continuous variation in the squint angle and the large range cell migration (RCM) throughout the data acquisition interval. A novel two-dimensional (2D) beam scanning mode for high-resolution wide swath (HRWS) imaging is proposed. The key to the novel imaging mode lies in the synchronous scanning of azimuth and range beams, allowing for a broader and more flexible imaging swath with a high geometric resolution. Azimuth beam scanning from fore to aft was used to improve the azimuth resolution, while range beam scanning was adopted to illuminate the oblique wide swath to avoid the large RCM and the serious swath width reduction. Compared with the conventional sliding spotlight mode, both the swath width and swath length could be extended. According to the echo model of this imaging mode, an echo signal preprocessing approach is proposed. The key points of this approach are range data extension and azimuth data upsampling. A designed system example with a resolution of 0.5 m, swath width of 60 km, and azimuth coverage length of 134 km is presented. Furthermore, a simulation experiment on point targets was carried out. Both the presented system example and imaging results of point targets validated the proposed imaging mode.

Effect of inclination angle and light source position on water temperature profile and productivity of solar still: an indoor experiment

Solar stills are generally used to obtain fresh and clean water from saline, brackish, and wastewater using solar energy. Many factors affect the performance of solar still, such as solar radiation, altitude, top cover inclination angle, etc. In this research, indoor solar still experiments have been carried out with different top cover inclination angles and light source positions with 7 hours of operating time. This research aims to study the effect of those two variables on water temperature profile and productivity of solar still. Halogen lamp was used as artificial light source. Three light source positions were selected based on the yearly solar azimuth and elevation angles data of Yogyakarta, Indonesia. The selected inclination angles were 20°, 30°, and 40°. Results demonstrated that light source position which related to incident angle of light at the top cover of solar still affected the water temperature profile in solar still. The water temperature profile decreased considerably when the angle of incident light was higher than 40°. Condensate productivity can be increased by using higher inclination angle of solar still top cover and highest condensate productivity of 518.75 mL/m2 can be obtained by using 40° of inclination angle. However, water temperature profile which affected by light source position must be taken into consideration when using higher inclination angle. Lower water temperature profile caused the decreasing of condensate productivity.

Antenna Directional Pattern Testing System Based on Multirotor Unmanned Aerial Vehicles

Obtaining azimuth data of antennas after installation on actual platforms (such as large aircraft, ships, etc.) is crucial for effectively analyzing the platform's impact on the antennas and facilitating optimization and improvement. Traditional testing methods are unable to accurately and efficiently acquire azimuth data due to significant differences between measurements in a dark room and the actual conditions. With the rapid development of drone technology, unmanned aerial platforms have been widely utilized in various engineering fields. Utilizing the flexibility of drones in three-dimensional space and their ability to be precisely controlled through RTK technology, it is possible to use drones equipped with test antennas to measure the azimuth pattern by receiving spectrum signals transmitted by antennas on real platforms. In order to achieve precise angle control, a gimbal system is designed to control the angle of the test antenna. The effectiveness of the entire testing system is verified through experimental results.

Sequential Bayesian seismic inversion for fracture parameters and fluid indicator in tilted transversely isotropic media

A rock permeated by tilted aligned fractures, which is common in the earth, can be considered as a tilted transversely isotropic (TTI) medium under the assumption of the long wavelength. We develop a feasible method to predict fracture parameters (namely weakness parameters and dip angle) and fluid type in TTI rock using azimuthal seismic data. Based on an approximate stiffness matrix, we first deduce a linear reflection coefficient of the gas-bearing TTI medium in terms of the new fluid indicator and fracture parameters. The reflection coefficient is then rewritten in the form of the Fourier series to decouple the fracture and skeleton-fluid information. Next, the sequential Bayesian inversion method is proposed, which consists of three steps. The first two steps conquer inversion instability owing to coupling of the fracture parameters by constructing a linear relationship between the second- and fourth-order Fourier coefficients. The last step aims at estimating the skeleton-fluid parameters. The sequential Bayesian inversion method alleviates the inversion ill-posedness that is caused by large differences in contributions of the fracture and skeleton-fluid parameters to the reflection coefficient. Synthetic and field cases prove our method is stable and rational in fracture and fluid detections. Finally, we draw the following conclusions from numerical experiments. The approximate stiffness coefficients and derived reflection coefficient are of satisfactory accuracy for the gas-bearing reservoir with low fracture density. The new fluid indicator is sensitive to fluid type but very weakly dependent on mineral composition and porosity. Deconvolution processing can improve the accuracies of different seismic components calculated using the discrete Fourier transformation.

Curvature attributes with the 3D seismic Kalman filter for fault opening description — An application to a shale oil reservoir in the Jimsar sag, Junggar Basin, Xinjiang

The large-scale shale-oil production in the Jimsar sag of the Junggar Basin is being aggressively developed. To improve unconventional production and make precise suggestions for horizontal well developments, fault interpretations using seismic data play an important role. The target reservoir in the Jimsar sag of the Junggar Basin has a comprehensive network of faults, according to the drilled wells and fault identification from the broadband azimuth and high-density 3D seismic data. Several reasons such as the integration between source and reservoir, the substantial abundance of organic matter, and the major reservoir plasticity result in different fault types, which then create different impacts on horizontal wells. We have developed a fault-type identification tool using the curvature attributes via the 3D seismic Kalman filter to provide a more accurate description of fault types. In contrast with previous studies, we derive the Kalman-curvature formulation in terms of space and time, by using a dynamically iterative optimization model. Our strategy reveals that various fault types (open faults, semiopen faults, and sealed faults) represent their characteristics associated with the 3D Kalman-curvature attributes. The resultant fault divisions are valid by combining the drilled information of lost circulation and fracturing crosstalk of the horizontal wells. High-quality field results validate the robustness of our algorithms.

Seismic pre-stack inversion for physical and anisotropic parameters in fractured shale reservoirs

AbstractThe estimation of physical and anisotropic parameters is of great importance for the characterization of fractured reservoirs. Vertical fractures developing in a laterally isotropic (VTI) setting are equivalent to orthotropic anisotropic (OA) media common in stratified fractured shale reservoirs. To obtain independent anisotropic and physical information, a novel reflection coefficient approximation containing physical and anisotropic parameters is derived to improve the stability of the inversion for orthotropic media. To simplify the equation for the reflection coefficient, an approximate rock physics model is constructed using the approximate theory of rock modulus. The estimated parameters are reduced from nine to six. The accuracy analysis reveals that the new reflection coefficient is appropriate and suitable for inversion. In addition, a stepwise Bayesian amplitude versus angle and azimuth (AVAZ) inversion method with smooth background constraints is developed to estimate the anisotropic and physical parameters from the azimuthal seismic data. The smooth background constraint improves the robustness of the inversion. And the stepwise inversion strategy solves the problem that the contribution of the fracture parameter to the reflection coefficient is smaller than the other parameters. Synthetic cases show that the proposed stepwise Bayesian AVAZ inversion method is feasible in estimating the anisotropic parameters for OA media even when the signal-to-noise ratio is 2. The field cases show that the proposed inversion method has good stability and robustness in predicting shale reservoirs with vertical or near-vertical fractures.

A High-Resolution Imaging Method for ISAR Based on Sparse Reconstruction

For the problem of first-order and second-order range migration in ISAR imaging under the condition of wide angle and wide bandwidth, a method for sparse azimuth data is proposed to obtain high-resolution ISAR images. After stretch processing, envelope alignment and residual video phase removal, the sparse recovery algorithm that sparse base is constructed by the Keystone transform is used to achieve range migration correction and the missing range profile reconstruction, and then the second-order phase estimation method based on fractional Fourier transform is used to estimate and compensate the second-order rotational phase. Simulation results show the method can effectively improve the imaging quality.

Azimuth Full-Aperture Processing of Spaceborne Squint SAR Data with Block Varying PRF

The block varying pulse repetition frequency (BV-PRF) scheme applied to spaceborne squint sliding-spotlight synthetic aperture radar (SAR) can resolve large-range cell migration (RCM) and reduce azimuth signal non-uniformity. However, in the BV-PRF scheme, different raw data blocks have different PRFs, and the raw data in each block are insufficiently sampled. To resolve the two problems, a novel azimuth full-aperture pre-processing method is proposed to handle the SAR raw data formed by the BV-PRF scheme. The key point of the approach is the resampling of block data with different PRFs and the continuous splicing of azimuth data. The method mainly consists of four parts: de-skewing, resampling, azimuth continuous combination, and Doppler history recovery. After de-skewing, the raw data with different PRFs can be resampled individually to obtain a uniform azimuth sampling interval, and an appropriate azimuth time shift is introduced to ensure the continuous combination of the azimuth signal. Consequently, the resulting raw data are sufficiently and uniformly sampled in azimuth, which could be well handled by classical SAR-focusing algorithms. Simulation results on point targets validate the proposed azimuth pre-processing approach. Furthermore, compared with methods to process SAR data with continuous PRF, the proposed method is more effective.