Investigation of the Technological Possibility of Laser Hardening of Stainless Steel 14Cr17Ni2 to a Deep Depth of the Surface

The article presents the results of a research of the process of laser hardening of steel 14Cr17Ni2 (AISI 431) by radiation of a high-power fiber laser LS-16. Assessment of the theoretically possible maximum depth in laser processing without additional beam transformations, the use of additional coatings and devices were shown. The results of experiments on increasing the depth of the hardened layer during laser processing by using scanning of the laser beam and optimally selected mode parameters without scanning are demonstrated. The influence of the number of passes on the depth of the hardened layer is investigated. The microstructure of hardened samples was studied and quantitative estimation of structural components was carried out. The microhardness of hardened samples at different modes of laser hardening was measured.

High Performance Computing on the Cloud Successfully Deployed for 3D Geosteering and Reservoir Mapping While Drilling

The successful drilling of horizontal wells targeting reservoir zones of interest can be challenged by uncertainties in geological interpretation, identification of structure, and properties of reservoirs and fluid distribution. Optimizing the well placement of high-angle wells in order to intercept the sweet spots is crucial for the total hydrocarbon recovery in any development field. Thus, the geosteering domain was implemented to provide in real time a reservoir mapping characterization together with directional control to achieve the key performance objectives. In the past, many innovative technologies have been introduced in geosteering discipline, among them lately the deep EM directional resistivity tool that provides 1D formation resistivity mapping while drilling. However, despite the fact of delivering a multilayer mapping of the reservoir structure up to tens of meters away from wellbore, the real-time interpretation can be limited by this type of inversion. Since it is a 1D approach, these inversions map resistive boundaries on the vertical axis and assume infinite extend in all other directions. Consequently, in a complex geological setting, 1D approximation may fall short of properly describing the reservoir structure. This communication describes how the introduction of the 2D azimuthal resistivity inversions while drilling was conducted and details the various innovations required in the domains of downhole logging while drilling (LWD) measurements transmission in addition to adaptation of inversion methodology for real-time deployment, mainly through the use of high-performance cloud computing. The final enablement was the execution of automated workflows to process and deliver these advanced inversions into an integrated 3D geomodelling software within the turnaround time of drilling operations. This novel technology provides, while drilling, a better understanding of the 3D geological environment and fluid distribution with a deep depth of investigation, as well as the required information to make support for geosteering decisions for optimal well positioning. Initial field deployments were successfully conducted in horizontal wells, and three examples are presented here. Those real cases, executed with wire-drilled-pipe or mud-pulse telemetries, demonstrated the benefits of integrating 2D azimuthal inversions into the current geosteering workflow to provide a complete 3D structural understanding of the reservoir while drilling. This communication documents in detail how such an approach led to operational efficiency improvements in the form of 3D reservoir mapping in real-time, supporting a strategic change in the original well to turn toward the sweet spot, which was located sideways from the planned trajectory.

Shallow Compaction Modeling and Upscaling: A One-Dimensional Analytical Solution and Upscaling

Natural depositional processes frequently give rise to the heterogeneous multilayer system, which is often overlooked but essential for the simulation of a geological process. The sediments undergo the large-strain process in shallow depth and the small-strain process in deep depth. With the transform matrix and Laplace transformation, a new method of solving multilayer small-strain (Terzaghi) and large-strain (Gibson) consolidations is proposed. The results from this work match the numerical results and other analytical solutions well. According to the method of transform matrix which can consider the integral properties of multilayer consolidation, a relevant upscaling method is developed. This method is more effective than the normally used weighted average method. Correspondingly, the upscaling results indicate that the upscaled properties of a multilayer system vary in the consolidation process.

Implementing Digital Edge Enhancers on Improved High-Resolution Aeromagnetic Signals for Structural-Depth Analysis around the Middle Benue Trough, Nigeria

Digital edge detector operations using magnetic derivatives in conjunction with spectra depth analysis were performed on high-resolution aeromagnetic signals to enhance the delineation and interpretation of depth, structural, and intrasedimentary features within the Middle Benue Trough (MBT) of North Central Nigeria, which could serve as a guide for mineral exploration. The derivatives revealed high-amplitude and short-wavelength anomalies over areas underlain by crystalline basement complexes, major volcanic zones, and aggregates of intrasedimentary volcanic and plutonic rocks. Geologic lineaments trending predominantly NE–SW and NW–SE, as well as minor trends of E–W and N–S, suggest that the area has undergone differential stress regimes across geologic time. The spectral depth analysis indicates a two-source depth model. The deep depth ranges from 1.9 to 6.1 km with an average of 3.9 km, whereas the shallow depth ranges between 0.3 and 1.9 km with an average of 0.8 km and is found to emanate from magnetic signals of post-Cretaceous near-surface igneous intrusions as well as other magnetized bodies embedded within the sediments. The spatial distribution of various hydrothermal minerals such as lead–zinc–barite deposits, as well as salt mineralization, is associated with the widespread Tertiary–recent magmatism and governed by pre-existing tectonic structures in the region.

Meningkatkan Daya Dukung Pondasi Tiang Pancang Gedung Abipraya Mojo Kabupaten Kediri Menggunakan Metode Begemann

The foundation is a lower structural element that serves to with stand the load of the upper structure. Pile foundation is one type of deep foundation, which is widely used in the construction of buildings. Pile foundation used in hard soil cases is located at a very deep depth. Abipraya Building is a building located in kediri regency which later functioned as a rural office. This study aims to increase the carrying capacity of pile foundation in the abipraya building project using the begemann method. Calculations carried out include the calculation of loading, carrying capacity, buckling factor and determination of foundation point. Based on the calculations obtained the results of axial load (sigma Vertical Ultimate) Σνυ of 99.70. with a single-pole carrying capacity of 38.89 tons and a group pole carrying capacity of 117,917 tons. These results will be planned the foundation of the stake with a diameter of 30 with a depth of 8 meters, amounting to 4 poles. Calculation factor buckling results in 194.14 kg/cm2 smaller than the allowed maximum 2400 kg/cm2. Thus, with the known components of the planning of the pile foundation, it can be used as a reference in the construction of the abipraya building.

An Image-Guided Network for Depth Edge Enhancement

With the rapid development of 3D coding and display technologies, numerous applications are emerging to target human immersive entertainments. To achieve a prime 3D visual experience, high accuracy depth maps play a crucial role. However, depth maps retrieved from most devices still suffer inaccuracies at object boundaries. Therefore, a depth enhancement system is usually needed to correct the error. Recent developments by applying deep learning to deep enhancement have shown their promising improvement. In this paper, we propose a deep depth enhancement network system that effectively corrects the inaccurate depth using color images as a guide. The proposed network contains both depth and image branches, where we combine a new set of features from the image branch with those from the depth branch. Experimental results show that the proposed system achieves a better depth correction performance than state of the art advanced networks. The ablation study reveals that the proposed loss functions in use of image information can enhance depth map accuracy effectively.