Interval Density Analysis From a Distributed Absolute Pressure Array

2021 ◽  
Author(s):  
Richard Hewlett ◽  
Stephen Pink ◽  
Jaideva Goswami ◽  
Daniel Debrosse ◽  
Charles Wright

Abstract The objective of this paper is to evaluate the effectiveness of a distributed pressure sensor array along the drillstring in identifying and quantifying fluid influx into the wellbore. As part of a real-time wired drillpipe (WDP) network, distributed sensors can be spaced along the network at varying intervals. In the fall of 2020, a test well was drilled where such a WDP network was utilized, involving 11 discrete sensor packages. These distributed sensors consisted of absolute annular and internal pressure transducers. From these distributed sensors, analysis of various intervals was examined for fluid effects including density analysis. This paper summarizes the findings of the tests and analyses. The WDP network (Craig, et al. 2013) is the underlying technology that allows for the distributed sensor array and the real-time processing of measured data. Each discrete sensor package is a node on the network. The industry-leading telemetry bandwidth of the WDP network allows for many sensor nodes. The test well drilled in the fall of 2020 gave an opportunity to place 11 sensor nodes along the drillstring. The real-time absolute pressure data collected from these nodes was analyzed for various intervals, calculating differential pressure between pressure sensor nodes and further calculating interval fluid density. The results of the distributed absolute pressure data provided many interesting observations. The effectiveness of the interval density for quick-look monitoring was greatly enhanced from the more traditional view of the raw pressure data alone. The effects of sensor spacing and sensitivity were easily observed. Tracking variations in fluid density as it transitions through the wellbore can provide insight into fluid mixing, fluid velocity, and transmission time. Transmission time through the various intervals can further provide insight into wellbore conditions. The slope and peak of interval fluid transitions help understand volumetric and specific density details of fluid transitions from events such as drilling mud pills and influx materials. This novel dataset showcases the power of a real-time distributed sensor array. Multiple intervals of interest can be examined, leading to a new level of wellbore understanding. Information concerning the wellbore fluid can aid in real-time decision making to optimize the wellbore and associated operations, while providing a new level of risk avoidance and safety factor.

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2830
Author(s):  
Sili Wang ◽  
Mark P. Panning ◽  
Steven D. Vance ◽  
Wenzhan Song

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests.


Author(s):  
Pilwon Hur ◽  
K. Alex Shorter ◽  
Elizabeth T. Hsiao-Wecksler

Posturographic data collected during quiet stance using force plates is widely used to assess postural stability [1]. Center of pressure (COP) is a commonly used experimental variable for several types of analyses. Traditionally, COP data have been analyzed using measures that describe the shape or speed of the trajectory [1]. Unfortunately, these parameters do not provide insight into the physiological system as a whole and have been shown to have questionable reliability [2].


2018 ◽  
Vol 14 (01) ◽  
pp. 4
Author(s):  
Wang Weidong

To improve the efficiency of the remote monitoring system for logistics transportation, we proposed a remote monitoring system based on wireless sensor network and GPRS communication. The system can collect information from the wireless sensor network and transmit the information to the ZigBee interpreter. The monitoring system mainly includes the following parts: Car terminal, GPRS transmission network and monitoring center. Car terminal mainly consists by the Zigbee microcontroller and peripherals, wireless sensor nodes, RFID reader, GPRS wireless communication module composed of a micro-wireless monitoring network. The information collected by the sensor communicates through the GPRS and the monitoring center on the network coordinator, sends the collected information to the monitoring center, and the monitoring center realizes the information of the logistics vehicle in real time. The system has high applicability, meets the design requirements in the real-time acquisition and information transmission of the information of the logistics transport vehicles and goods, and realizes the function of remote monitoring.


2005 ◽  
Vol 1 (3-4) ◽  
pp. 345-354 ◽  
Author(s):  
Dibyendu Chakrabarti ◽  
Subhamoy Maitra ◽  
Bimal Roy

Key pre-distribution is an important area of research in Distributed Sensor Networks (DSN). Two sensor nodes are considered connected for secure communication if they share one or more common secret key(s). It is important to analyse the largest subset of nodes in a DSN where each node is connected to every other node in that subset (i.e., the largest clique). This parameter (largest clique size) is important in terms of resiliency and capability towards efficient distributed computing in a DSN. In this paper, we concentrate on the schemes where the key pre-distribution strategies are based on transversal design and study the largest clique sizes. We show that merging of blocks to construct a node provides larger clique sizes than considering a block itself as a node in a transversal design.


2021 ◽  
Vol 92 (3) ◽  
pp. 035113
Author(s):  
Huan Liu ◽  
Changfeng Zhao ◽  
Xiaobin Wang ◽  
Zehua Wang ◽  
Jian Ge ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1922
Author(s):  
Gwang Su Kim ◽  
Yumin Park ◽  
Joonchul Shin ◽  
Young Geun Song ◽  
Chong-Yun Kang

The breath gas analysis through gas phase chemical analysis draws attention in terms of non-invasive and real time monitoring. The array-type sensors are one of the diagnostic methods with high sensitivity and selectivity towards the target gases. Herein, we presented a 2 × 4 sensor array with a micro-heater and ceramic chip. The device is designed in a small size for portability, including the internal eight-channel sensor array. In2O3 NRs and WO3 NRs manufactured through the E-beam evaporator’s glancing angle method were used as sensing materials. Pt, Pd, and Au metal catalysts were decorated for each channel to enhance functionality. The sensor array was measured for the exhaled gas biomarkers CH3COCH3, NO2, and H2S to confirm the respiratory diagnostic performance. Through this operation, the theoretical detection limit was calculated as 1.48 ppb for CH3COCH3, 1.9 ppt for NO2, and 2.47 ppb for H2S. This excellent detection performance indicates that our sensor array detected the CH3COCH3, NO2, and H2S as biomarkers, applying to the breath gas analysis. Our results showed the high potential of the gas sensor array as a non-invasive diagnostic tool that enables real-time monitoring.


2006 ◽  
Author(s):  
Mike Parker ◽  
Robert N. Bradford ◽  
Laurence Ward Corbett ◽  
Robin Noel Heim ◽  
Christina Leigh Isakson ◽  
...  

2014 ◽  
Vol 169 ◽  
pp. 443-453 ◽  
Author(s):  
Jeremiah J. Shepherd ◽  
Lingxi Zhou ◽  
William Arndt ◽  
Yan Zhang ◽  
W. Jim Zheng ◽  
...  

More and more evidence indicates that the 3D conformation of eukaryotic genomes is a critical part of genome function. However, due to the lack of accurate and reliable 3D genome structural data, this information is largely ignored and most of these studies have to use information systems that view the DNA in a linear structure. Visualizing genomes in real time 3D can give researchers more insight, but this is fraught with hardware limitations since each element contains vast amounts of information that cannot be processed on the fly. Using a game engine and sophisticated video game visualization techniques enables us to construct a multi-platform real-time 3D genome viewer. The game engine-based viewer achieves much better rendering speed and can handle much larger amounts of data compared to our previous implementation using OpenGL. Combining this viewer with 3D genome models from experimental data could provide unprecedented opportunities to gain insight into the conformation–function relationships of a genome.


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