Integrated Hydraulic Fracturing and Well-Test Data Analytics using R

1. Abstract Various datasets are generated during hydraulic fracturing, flowback- and well-testing operations, which require consistent integration to lead to high-quality well performance interpretations. An automated digital workflow has been created to integrate and analyze the data in a consistent manner using the open-source programming language R. This paper describes the workflow, and it explains how it automatically generates well performance models and how it analyzes raw diagnostic fracture injection test (DFIT) data using numerical algorithms and Machine Learning. This workflow is successfully applied in a concession area located in the center of the Sultanate of Oman, where to date a total of 25+ tight gas wells are drilled, hydraulically fractured and well-tested. It resulted in an automated and standardized way of working, which enabled identifying trends leading to improved hydraulic fracturing and well-testing practices.

HActivityNet: A Deep Convolutional Neural Network for Human Activity Recognition

Human Activity Recognition (HAR), a vast area of a computer vision research, has gained standings in recent years due to its applications in various fields. As human activity has diversification in action, interaction, and it embraces a large amount of data and powerful computational resources, it is very difficult to recognize human activities from an image. In order to solve the computational cost and vanishing gradient problem, in this work, we have proposed a revised simple convolutional neural network (CNN) model named Human Activity Recognition Network (HActivityNet) that is automatically extract and learn features and recognize activities in a rapid, precise and consistent manner. To solve the problem of imbalanced positive and negative data, we have created two datasets, one is HARDataset1 dataset which is created by extracted image frames from KTH dataset, and another one is HARDataset2 dataset prepared from activity video frames performed by us. The comprehensive experiment shows that our model performs better with respect to the present state of the art models. The proposed model attains an accuracy of 99.5% on HARDatase1 and almost 100% on HARDataset2 dataset. The proposed model also performed well on real data.

Inheritance of plant height, straw yield and flag leaf area in MBB x Gaviota durum wheat (Triticum durum Desf.) cross

<p class="042abstractstekst">Plant height, straw mass and flag leaf area are recognized by physiologists as morphological markers of drought stress tolerance. Developing varieties intended for arid and semi-arid zones need to select for these traits. Understanding the genetic control of a given trait helps breeder to handle the segregating populations under study in a more efficient and consistent manner by choosing the best breeding method available to realize significant genetic advance. For this purpose, six generations: parents, F1, F2, BC1, BC2, derived from MBB x ‘Gaviota’ durum wheat (<em>Triticum durum </em>Desf.) cross were grown to investigate the nature of gene action involved in the inheritance pattern of the three traits. The results indicated that the six-parameter model fitted the best the data related to the variability present in the generation means of the studied traits. Generation mean analysis indicated that non-allelic interactions were important factors controlling the expression of these characters with complementary type of gene action governing FLA and STW inheritance. High heritability estimates, moderate to high expected responses to selection, significant genetic correlations with grain yield and greater role of non-additive effects in controlling the inheritance of the three studied traits suggested that breeding methods exploiting both fixable and non-fixable components be applied to break unfavorable linkage and to accumulate useful genes in the base population, followed by mono-trait or index based selection in late advanced generations.</p>

A Pusher and a Clip Applied to Hind Paws Under Isoflurane Sedation to Evaluate Neuropathic Pain in a CCI Model

: Rodent behavior assessments have been developed to evaluate pain. However, their fidgety activity and reactivity to human contact make it hard to activate animals in a consistent manner and get uniform and trustworthy responses. The present study was performed on prairie voles (aged 8 weeks). Sham (7 male prairie voles) and chronic constriction injury (CCI) (8 male prairie voles) rodents were investigated before surgery and four and seven days later. Each animal was assessed for nociceptive behavior. Pressure and mechanical threshold tests were conducted by the application of three different pushers to the center of hind paws and arterial clips to the toes while sedated with isoflurane. The CCI affected right lower extremity prominently increased nociceptive behavior scores four and seven days after the experiment, and the CCI affected right hind paw prominently decreased pressure and mechanical threshold tests four and seven days after the experiment . The pressure and mechanical thresholds were relevant to the scorings of nociceptive behavior in CCI model animals.

The Effect of Tongue-Tie Release on Speech Articulation and Intelligibility

Objective The relationship between ankyloglossia and speech is controversial. The objective of this study was to determine the effect of tongue-tie release on speech articulation and intelligibility. Methods A prospective cohort study was conducted. Pediatric patients (>2 years of age) being referred for speech concerns due to ankyloglossia were assessed by a pediatric otolaryngologist, and speech articulation was formally assessed by a speech language pathologist using the Goldman-Fristoe Test of Articulation 2 (GFTA-2). Patients then underwent a tongue-tie release procedure in clinic. After 1 month, speech articulation was reassessed with GFTA-2. Audio-recordings of sessions were evaluated by independent reviewers to assess speech intelligibility before and after tongue-tie release. Results Twenty-five participants were included (mean age 3.7 years; 20 boys). The most common speech errors identified were phonological substitutions (80%) and gliding errors (56%). Seven children (28%) had abnormal lingual-alveolar and interdental sounds. Most speech sound errors (87.9%) were age/developmentally appropriate. GFTA-2 standard scores before and after tongue-tie release were 85.61 (SD 9.75) and 87.54 (SD 10.21), respectively, (P=.5). Mean intelligibility scores before and after tongue-tie release were 3.15 (SD .22) and 3.21 (SD .31), respectively, (P=.43). Conclusion The majority of children being referred for speech concerns thought to be due to ankyloglossia had age-appropriate speech errors at presentation. Ankyloglossia was not associated with isolated tongue mobility related speech articulation errors in a consistent manner, and there was no benefit of tongue-tie release in improving speech articulation or intelligibility.

Drilling Automation: The Step Forward for Improving Safety, Consistency, and Performance in Onshore Gas Drilling

In the current oil and gas drilling industry, the modernization of rig fleets has been shifting toward high mobility, artificial intelligence, and computerized systems. Part of this shift includes a move toward automation. This paper summarizes the successful application of a fully automated workflow to drill a stand, from slips out to slips back in, in a complex drilling environment in onshore gas. Repeatable processes with adherence to plans and operating practices are a key requirement in the implementation of drilling procedures and vital for optimizing operations in a systematic way. A drilling automation solution has been deployed in two rigs enabling the automation of both pre-connection and post-connection activities as well as rotary drilling of an interval equivalent to a typical drillpipe stand (approximately 90 ft) while optimizing the rate of penetration (ROP) and managing drilling dysfunctionalities, such as stick-slip and drillstring vibrations in a consistent manner. So far, a total of nine wells have been drilled using this solution. The automation system is configured with the outputs of the drilling program, including the drilling parameters roadmap, bottomhole assembly tools, and subsurface constraints. Before drilling every stand, the driller is presented with the planned configuration and can adjust settings whenever necessary. Once a goal is specified, the system directs the rig control system to command the surface equipment (draw works, auto-driller, top drive, and pumps). Everything is undertaken in the context of a workflow that reflects standard operating procedures. This solution runs with minimal intervention from the driller and each workflow contextual information is continuously displayed to the driller thereby giving him the best capacity to monitor and supervise the operational sequence. If drilling conditions change, the system will respond by automatically changing the sequence of activities to execute mitigation procedures and achieve the desired goal. At all times, the driller has the option to override the automation system and assume control by a simple touch on the rig controls. Prior to deployment, key performance indicators (KPI), including automated rig state-based measures, were selected. These KPIs are then monitored while drilling each well with the automation system to compare performance with a pre-deployment baseline. The solution was used to drill almost 60,000 ft of hole section with the system in control, and the results showed a 20% improvement in ROP with increased adherence to pre-connection and post-connection operations. Additionally, many lessons were learned from the use and observation of the automation workflow that was used to drive continuous improvement in efficiency and performance over the course of the project. This deployment was the first in the region and the system is part of a comprehensive digital well construction solution that is continuously enriched with new capabilities. This adaptive automated drilling solution delivered a step change in performance, safety, and consistency in the drilling operations.

The Interplay of Interstitial and Substitutional Copper in Zinc Oxide

Cu impurities are reported to have significant effects on the electrical and optical properties of bulk ZnO. In this work, we study the defect properties of Cu in ZnO using hybrid quantum mechanical/molecular mechanical (QM/MM)–embedded cluster calculations based on a multi-region approach that allows us to model defects at the true dilute limit, with polarization effects described in an accurate and consistent manner. We compute the electronic structure, energetics, and geometries of Cu impurities, including substitutional and interstitial configurations, and analyze their effects on the electronic structure. Under ambient conditions, CuZn is the dominant defect in the d9 state and remains electronically passive. We find that, however, as we approach typical vacuum conditions, the interstitial Cu defect becomes significant and can act as an electron trap.

Leveraging Large Subsurface Data and Associated Uncertainties to Build High Quality 3D Structural Model

Objectives/Scope At brownfield development stage, dealing with diverse and large amount of data makes it challenging to integrate them all in a consistent manner to build a prime structural model. Like many others, the studied field consists of several-stacked reservoirs featuring many faults and close to a thousand drilled wells with vertical, slanted and horizontal trajectories. On top of that, many horizontal wells are targeting thin carbonate layers for which tightly spaced data points often result in conflicting observations. Consequently, horizontal and deviated wells are commonly discarded from structural modelling, leaving substantial and valuable information unused. Some of these wells may be indirectly accounted through the introduction of pseudo-wells, making the modelling workflow tedious, user-dependent and therefore difficult to repeat. Methods, Procedures, Process ’It's better to be approximately right than exactly wrong’ quoted by Carveth Read, 18th century. Accordingly, every physical measurement, even from the most modern and sophisticated tools, is subject to some uncertainty. Therefore, assessing the uncertainty related to each input data is paramount in this method. Integrated teamwork between geologists, geophysicists and drilling specialists lead to a thorough analysis of each data feeding the process of structural model building while providing best uncertainty estimates. The ranges were specified for ∼1000 well trajectories, ∼16000 geological markers, 3 seismic travel time maps, 3 interval velocities and 59 thickness maps. All available data are used in a consistent manner to minimize the depth uncertainty. The accuracy is further improved by linking together all surfaces in a multi-layered model. In addition, this methodology considers both large scale spatial continuity capturing structural trends and more local scale incorporating inter-well variations of thickness due to sedimentological controls. Results, Observations, Conclusions After following this approach, all subsurface data started to come in agreement and resulted in more geological architectures. As an example, Figure 1 shows a cross-section along a well that drilled in B4 target layer which average thickness of 6 ft. As illustrated in the left figure, classical workflow using vertical wells and some pseudo-wells resulted in an anomalous pull-up structure and overall wavy non-geological geometry. Moreover, the well shows that it is in non-reservoir dense layer even though the well in the reservoir based on the zone log interpretation. However, the right figure shows that considering horizontal wells and uncertainties help to integrate all subsurface data with improved consistency where the structure model is smoother & more geological, plus the well is correctly placed in the targeted reservoir. Novel/Additive Information This approach will make the studied field one of the first brownfields that incorporated all data in consistent manner without pseudo-wells to build 3D structural model. It will bring considerable value to reduce uncertainties during subsequent property and dynamic modelling stages.

Potential Fault Displacement Hazard Assessment Using Stochastic Source Models: A Retrospective Evaluation for the 1999 Hector Mine Earthquake

Surface fault displacement due to an earthquake affects buildings and infrastructure in the near-fault area significantly. Although approaches for probabilistic fault displacement hazard analysis have been developed and applied in practice, there are several limitations that prevent fault displacement hazard assessments for multiple locations simultaneously in a physically consistent manner. This study proposes an alternative approach that is based on stochastic source modelling and fault displacement analysis using Okada equations. The proposed method evaluates the fault displacement hazard potential due to a fault rupture. The developed method is applied to the 1999 Hector Mine earthquake from a retrospective perspective. The stochastic-source-based fault displacement hazard analysis method successfully identifies multiple source models that predict fault displacements in close agreement with observed GPS displacement vectors and displacement offsets along the fault trace. The case study for the 1999 Hector Mine earthquake demonstrates that the proposed stochastic-source-based method is a viable option in conducting probabilistic fault displacement hazard analysis.

The early childhood inhibitory touchscreen task: A new measure of response inhibition in toddlerhood and across the lifespan

Research into the earliest development of inhibitory control is limited by a lack of suitable tasks. In particular, commonly used inhibitory control tasks frequently have too high language and working memory demands for children under 3 years of age. Furthermore, researchers currently tend to shift to a new set of inhibitory control tasks between infancy, toddlerhood, and early childhood, raising doubts about whether the same function is being measured. Tasks that are structurally equivalent across age could potentially help resolve this issue. In the current report, a new response inhibition task, the Early Childhood Inhibitory Touchscreen Task (ECITT), was developed. This task can be minimally modified to suit different ages, whilst remaining structurally equivalent. In the new task, participants have to overcome a tendency to respond to a frequently rewarded location on a touchscreen and instead make an alternative response. The ECITT was validated in three independent studies (with additional data, N = 166, reported in Supporting Information). In Study 1 (N = 81), cross-sectional data indicated that inhibitory performance on the task improved significantly between 24 and 30 months of age. In Study 2 (N = 38), longitudinal data indicated steady improvement in inhibitory control between 18, 21 and 24 months, with significant stability in individual performance differences between each consecutive age in terms of accuracy (but not in terms of reaction time). Finally, in Study 3 (N = 64), inhibitory performance on a faster-paced version of the same task showed a similar developmental course across the lifespan (4–84 years) to other response inhibition tasks and was significantly correlated with Stop-signal performance. The ECITT extends the assessment of response inhibition earlier than previous tasks–into early toddlerhood. Because the task is simple and structurally equivalent across age, future longitudinal studies should benefit from using the ECITT to investigate the development of inhibitory control in a consistent manner across the toddler years and beyond.