DRVision Technologies (United States)

Abstract High-resolution acoustic imaging technology has been developed and deployed to map the downhole location and orientation of fiber optic lines in unconventional oil and gas and carbon capture wells. Fiber optic installations are long term monitoring solutions providing continuous measurement of temperature, sound, or strain. These fiber lines provide significant insight into the operation and optimization of downhole assets but require a large capital investment, typically upwards of a million dollars. By accurately mapping fiber optic lines, operators can prevent damaging or perforating through these costly systems during completion and production operations. High-resolution acoustic imaging technology allows operators to directly locate and map in-situ fiber optic systems at logging speeds up to ten times faster, with high accuracy, and more efficiently than legacy technologies by overcoming the requirement to install additional costly detection components. The unique sensor probe employs a circumferential array design, comprised of up to 512 individual elements which are electronically controlled from advanced imaging software. The integration of machine vision algorithms has led to a 100% success rate at detecting, orientating, and mapping of fiber optic lines to prevent damaging these costly and critical monitoring installations. Through a series of validation tests and field applications, this paper details how the solid-state imaging probe was used to identify the submillimetric indentations made at each fiber clamps installation. These contact points indicate the depth and phase orientation of each clamp in a well, enabling the generation of a high-resolution fiber optics system map. While legacy ultrasonic tools rely on a direct reflection principle, this novel, intra-steel imaging technology measures diffuse acoustic reflections at any point on, or inside of, the casing steel. Diffuse reflections are highly sensitive to indentations and markings on the casing surfaces; this removes the legacy-technology requirements for excessively slow logging speeds and the installation of costly steel detection bars. Following successful validation testing, this technology was field deployed and successfully located, oriented, and mapped all the fiber optic clamps ahead of perforating the casing of a carbon capture well. The platform imaged and mapped over 2,060 clamp contact points with a sub-radian azimuthal or phase resolution. In addition to this, high- resolution acoustics have shown fiber optic systems wrap around the casing circumference multiple times, highlighting the inability for fiber optic systems to be accurately installed and oriented. Using this dataset, the operator effectively executed subsequent perforation activities without damaging the fiber optic lines used to monitor the well and reservoir.

We present a summary of the full calculation of the axial, scalar and tensor flavor diagonal charges of the nucleon carried out using Wilson-clover fermions on eight ensembles generated using 2+1+1-flavors of highly improved staggered quarks (HISQ) by the MILC collaboration. We also give results for the $3\times 3$ matrix of renormalization factors between the RI-sMOM and $\overline{\rm MS}$ scheme for the 2+1 flavor theory that include flavor mixing. Preliminary results for $g_{A,S,T}^{u,d,s}$ are presented in the $\overline{\rm MS}$ scheme at scale 2 GeV.

Summary A novel high-resolution acoustic imaging technology was developed for the identification of downhole obstructions, restrictions, and casing damage in real time. This system is the first downhole imaging platform that incorporates an articulated robotic head to capture a dimensionally accurate three-dimensional (3D) view of the area of interest with a 0.00016-in2 resolution. The imaging head can navigate a well with a positional precision of 0.0005-in; it provides a 3D reconstruction of the adjacent casing and any obstruction that may be of interest. These real-time images can be captured in any fluid, including brine, oil, water, drilling fluids, and bitumen. The device can replace conventional lead impression blocks and optical-based cameras, both of which have struggled to provide definitive results in challenging environments associated with hydraulically fractured wells. Multi-axis robotics allows navigation through the area of interest and provides the operator with a real-time assessment of casing condition or fish location; it removes any ambiguity associated with the size, location, and orientation of a well obstruction. The rendered 3D point-cloud of data is displayed in real time to field personnel on surface allowing for operators to start planning and executing remedial action with high certainty before the tool has come to surface. This paper outlines the novel technology background and a case study of field deployment. The tool was deployed in the field as a three-dimensional method to overcome inconsistent, low-resolution, and ambiguous results provided by legacy technologies still used in industry.

Marketing is defined as the action or business of promoting and selling products or services. In order for the metalcasting industry to survive and thrive, it must be able to market itself and its products to its customers, next generation of employees and the communities in which its facilities reside. Unfortunately, this has not always been done in a consistent fashion across the industry. This paper will discuss the importance of marketing strategy and suggest some actions for the metalcasting industry to take.

Sensory data integration is an important task in human brain for multimodal processing as well as in machine learning for multisensor processing. α-integration was proposed by Amari as a principled way of blending multiple positive measures (e.g., stochastic models in the form of probability distributions), providing an optimal integration in the sense of minimizing the α-divergence. It also encompasses existing integration methods as its special case, e.g., weighted average and exponential mixture. In α-integration, the value of α determines the characteristics of the integration and the weight vector w assigns the degree of importance to each measure. In most of the existing work, however, α and w are given in advance rather than learned. In this paper we present two algorithms, for learning α and w from data when only a few integrated target values are available. Numerical experiments on synthetic as well as real-world data confirm the proposed method's effectiveness.

This study was conducted to compare the hydrogen embrittlement (HE) resistance of austempered 4340 steel with quenched and tempered (Q&T) 4340 steel with an identical yield strength (YS) of 1340 MPa (194 ksi). A baseline comparison showed that the austempered steel with a lower bainite microstructure exhibited higher hardness, tensile strengths, Charpy V-notch (CVN) impact toughness, and ductility at both low 233 K (−40 F) and ambient temperatures, as compared to the Q&T steel with a martensite microstructure. After machining and just prior to testing, subsized CVN specimens and notched bend specimens were immersed in hydrochloric acid-water baths. The HE resistance was higher for the austempered steel than the Q&T steel. No differences in room-temperature CVN energy resulted from hydrogen charging of the austempered and Q&T steels vs their unexposed counterparts. However, in the notched bend specimens, the hydrogen charging caused significant peak load decreases (40 pct) for the Q&T steel, while the austempered steel exhibited only small (6 pct) decreases in peak load. Intergranular (IG) fracture occurred solely in the charged Q&T bend samples, which is further evidence of their embrittlement.