Journey of Effectively Using Real-Time Production Surveillance Tool in Digital Transformation and Well, Reservoir and Facility Management Improvements

2021 ◽  
Author(s):  
Sambit Kumar Sahu ◽  
Christophe Lauwerys ◽  
Zulfikri Abdullah ◽  
Mariana Jamil Muhammad ◽  
Divya Agrawal
Keyword(s):  
Real Time ◽  
Reservoir Management ◽  
Facility Management ◽  
Digital Transformation ◽  
Critical Parameters ◽  
Corrosion Monitoring ◽  
Control Line ◽  
Success Stories ◽  
Allocation Process ◽  
Wide Range

Abstract In 2014, SPE-167857-MS was published highlighting how Real-Time Surveillance using the Shell proprietary Production Universe (PU) application helped to reduce deferment, improve production allocation, optimize test unit capacity, and track well operating envelope in Brunei Shell Petroleum BSP (company) operations in South East Asia. Since then, there has been significant progress in the application of PU to help the company meet Wells Reservoir Management (WRFM) requirements and Operational Excellence standards in areas such as Platform Production Reconciliation, Well Modeling, Production Estimation, and Exception based Surveillance helping the company to improve their Hydrocarbon and Energy Accounting. The wider introduction of the PU application in the allocation process significantly helped in Hydrocarbon Accounting (HCA), helping company's journey in moving from monthly to daily allocation and assisting to improve the field reconciliation factor (RF). The utilization of PU has also facilitated real-time monitoring of production parameters supporting engineers to safely and efficiently operate their wells within the Operating Envelopes while adhering to reservoir management guidelines. The optimization engine of the PU has been used to maximize the production of company contributing to two major success stories of Real-Time Condensate Optimization in a Gas-Constraint system and Gas Lift Optimization in a platform with limited lift gas availability amongst the producing wells. An Integrated Production Monitoring and Optimization System (IPMOS) provides asset-wide advice on optimally producing company's well within the constraints imposed by limitations on pipeline capacity, compressor throughput, and remote operability while satisfying customer demands. PU is additionally being used in Proactive Technical Monitoring (PTM) of rotating equipment to identify the critical parameters operating outside the set limits in an exception-based format. PU alerts & alarms have been configured in a wide range of operational monitoring such as Ensure Safe Production (ESP), Chemical Injection, Annulus Pressure Monitoring(APM), Control-Line pressure, Erosion-Corrosion Monitoring System(ECMS) to alert Production Engineers in case of any discrepancy or exception-based format for them to take remedial actions. This paper will explain how each of the above applications in PU has helped company in its journey of closing its gap to potential and achieving the digital transformation of its operations.

Chromo-fluorogenic sensors for chemical warfare agents in real-time analysis: journey towards accurate detection and differentiation

2021 ◽  
Vol 57 (28) ◽  
pp. 3430-3444
Author(s):  
Vinod Kumar
Keyword(s):  
Real Time ◽  
Chemical Warfare Agents ◽  
Chemical Warfare ◽  
Chemical Probes ◽  
Time Analysis ◽  
Specific Detection ◽  
Success Stories ◽  
Real Time Analysis ◽  
Warfare Agents ◽  
Unique Chemical

This article describes our journey and success stories in the development of chemical warfare detection, detailing the range of unique chemical probes and methods explored to achieve the specific detection of individual agents in realistic environments.

A New Flexible Rapid Thermal Processing System

1995 ◽  
Vol 389 ◽  
Author(s):  
K. C. Saraswat ◽  
Y. Chen ◽  
L. Degertekin ◽  
B. T. Khuri-Yakub
Keyword(s):  
Control System ◽  
Real Time ◽  
Processing System ◽  
Process Conditions ◽  
Temperature Uniformity ◽  
Real Time Control ◽  
Wafer Temperature ◽  
Time Control ◽  
Wide Range ◽  
Optical Flux

ABSTRACTA highly flexible Rapid Thermal Multiprocessing (RTM) reactor is described. This flexibility is the result of several new innovations: a lamp system, an acoustic thermometer and a real-time control system. The new lamp has been optimally designed through the use of a “virtual reactor” methodology to obtain the best possible wafer temperature uniformity. It consists of multiple concentric rings composed of light bulbs with horizontal filaments. Each ring is independently and dynamically controlled providing better control over the spatial and temporal optical flux profile resulting in excellent temperature uniformity over a wide range of process conditions. An acoustic thermometer non-invasively allows complete wafer temperature tomography under all process conditions - a critically important measurement never obtained before. For real-time equipment and process control a model based multivariable control system has been developed. Extensive integration of computers and related technology for specification, communication, execution, monitoring, control, and diagnosis demonstrates the programmability of the RTM.

scholarly journals Distributed X-ray photon correlation spectroscopy data reduction using Hadoop MapReduce

2018 ◽  
Vol 25 (4) ◽  
pp. 1135-1143 ◽  
Author(s):  
Faisal Khan ◽  
Suresh Narayanan ◽  
Roger Sersted ◽  
Nicholas Schwarz ◽  
Alec Sandy
Keyword(s):  
Real Time ◽  
Photon Correlation Spectroscopy ◽  
Correlation Spectroscopy ◽  
Frame Rate ◽  
Computational Techniques ◽  
Complex Materials ◽  
Photon Correlation ◽  
X Ray ◽  
Wide Range ◽  
Recent Developments

Multi-speckle X-ray photon correlation spectroscopy (XPCS) is a powerful technique for characterizing the dynamic nature of complex materials over a range of time scales. XPCS has been successfully applied to study a wide range of systems. Recent developments in higher-frame-rate detectors, while aiding in the study of faster dynamical processes, creates large amounts of data that require parallel computational techniques to process in near real-time. Here, an implementation of the multi-tau and two-time autocorrelation algorithms using the Hadoop MapReduce framework for distributed computing is presented. The system scales well with regard to the increase in the data size, and has been serving the users of beamline 8-ID-I at the Advanced Photon Source for near real-time autocorrelations for the past five years.

Digital Workflow to Enhance Reservoir Management Strategies for A Complex Oil Field Through Real Time and Advanced Engineering Monitoring Solution

2021 ◽  
Author(s):  
Julieta Alvarez ◽  
Oswaldo Espinola ◽  
Luis Rodrigo Diaz ◽  
Lilith Cruces
Keyword(s):  
Real Time ◽  
Reservoir Characterization ◽  
Management Strategies ◽  
Reservoir Management ◽  
Gas Production ◽  
Oil Field ◽  
Oil Reservoirs ◽  
Production Operation ◽  
Digital Workflow ◽  
Operational Decisions

Abstract Increase recovery from mature oil reservoirs requires the definition of enhanced reservoir management strategies, involving the implementation of advanced methodologies and technologies in the field's operation. This paper presents a digital workflow enabling the integration of commonly isolated elements such as: gauges, flowmeters, inflow control devices; analysis methods and data, used to improve scientific understanding of subsurface flow dynamics and determine improved operational decisions that support field's reservoir management strategy. It also supports evaluation of reservoir extent, hydraulic communication, artificial lift impact in the near-wellbore zone and reservoir response to injected fluids and coning phenomenon. This latest is used as an example to demonstrate the applicability of this workflow to improve and support operational decisions, minimizing water and gas production due to coning, that usually results in increasing production operation costs and it has a direct impact decreasing reservoir energy in mature saturated oil reservoirs. This innovative workflow consists on the continuous interpretation of data from downhole gauges, referred in this paper as data-driven; as well as analytical and numerical simulation methodologies using real-time raw data as an input, referred in this paper as model-driven, not commonly used to analyze near wellbore subsurface phenomena like coning and its impact in surface operation. The resulting analyses are displayed through an extensive visualization tool that provides instant insight to reservoir characterization and productivity groups, improving well and reservoir performance prediction capabilities for complex reservoirs such as mature saturated reservoirs with an associated aquifer, where undesired water and gas production is a continuous challenge that incorporates unexpected operational expenses.

A Novel Corrosion Monitoring and Prediction System Utilizing Advanced Artificial Intelligence

2021 ◽  
Author(s):  
Klemens Katterbauer ◽  
Waleed Dokhon ◽  
Fahmi Aulia ◽  
Mohanad Fahmi
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Salt Water ◽  
Oil And Gas Industry ◽  
Training Dataset ◽  
Metal Loss ◽  
Corrosion Monitoring ◽  
Prediction System ◽  
Well Performance ◽  
Data Driven Approach

Abstract Corrosion in pipes is a major challenge for the oil and gas industry as the metal loss of the pipe, as well as solid buildup in the pipe, may lead to an impediment of flow assurance or may lead to hindering well performance. Therefore, managing well integrity by stringent monitoring and predicting corrosion of the well is quintessential for maximizing the productive life of the wells and minimizing the risk of well control issues, which subsequently minimizing cost related to corrosion log allocation and workovers. We present a novel supervised learning method for a corrosion monitoring and prediction system in real time. The system analyzes in real time various parameters of major causes of corrosion such as salt water, hydrogen sulfide, CO2, well age, fluid rate, metal losses, and other parameters. The data are preprocessed with a filter to remove outliers and inconsistencies in the data. The filter cross-correlates the various parameters to determine the input weights for the deep learning classification techniques. The wells are classified in terms of their need for a workover, then by the framework based on the data, utilizing a two-dimensional segmentation approach for the severity as well as risk for each well. The framework was trialed on a probabilistically determined large dataset of a group of wells with an assumed metal loss. The framework was first trained on the training dataset, and then subsequently evaluated on a different test well set. The training results were robust with a strong ability to estimate metal losses and corrosion classification. Segmentation on the test wells outlined strong segmentation capabilities, while facing challenges in the segmentation when the quantified risk for a well is medium. The novel framework presents a data-driven approach to the fast and efficient characterization of wells as potential candidates for corrosion logs and workover. The framework can be easily expanded with new well data for improving classification.

Case Study- Real Time Downhole Telemetry CCL and Tension Compression, a Differentiator for Successful Manipulation of ICD's in Horizontal Wells

2021 ◽  
Author(s):  
Usman Ahmed ◽  
Zhiheng Zhang ◽  
Ruben Ortega Alfonzo
Keyword(s):  
Saudi Arabia ◽  
Real Time ◽  
Oil Recovery ◽  
Horizontal Wells ◽  
Differential Pressure ◽  
Successful Operation ◽  
Coiled Tubing ◽  
Electric Line ◽  
Wide Range ◽  
Ict System

Abstract Horizontal well completions are often equipped with Inflow Control Devices (ICDs) to optimize flow rates across the completion for the whole length of the interval and to increase the oil recovery. The ICD technology has become useful method of optimizing production from horizontal wells in a wide range of applications. It has proved to be beneficial in horizontal water injectors and steam assisted gravity drainage wells. Traditionally the challenges related to early gas or water breakthrough were dealt with complex and costly workover/intervention operations. ICD manipulation used to be done with down-hole tractor conveyed using an electric line (e-line) cable or by utilization of a conventional coiled tubing (CT) string. Wellbore profile, high doglegs, tubular ID, drag and buoyancy forces added limitations to the e-line interventions even with the use of tractor. Utilization of conventional CT string supplement the uncertainties during shifting operations by not having the assurance of accurate depth and forces applied downhole. A field in Saudi Arabia is completed with open-hole packer with ICD completion system. The excessive production from the wells resulted in increase of water cut, hence ICD's shifting was required. As operations become more complex due to fact that there was no mean to assure that ICD is shifted as needed, it was imperative to find ways to maximize both assurance and quality performance. In this particular case, several ICD manipulating jobs were conducted in the horizontal wells. A 2-7/8-in intelligent coiled tubing (ICT) system was used to optimize the well intervention performance by providing downhole real-time feedback. The indication for the correct ICD shifting was confirmed by Casing Collar Locator (CCL) and Tension & Compression signatures. This paper will present the ICT system consists of a customized bottom-hole assembly (BHA) that transmits Tension, compression, differential pressure, temperature and casing collar locator data instantaneously to the surface via a nonintrusive tube wire installed inside the coiled tubing. The main advantages of the ICT system in this operation were: monitoring the downhole force on the shifting tool while performing ICD manipulation, differential pressure, and accurately determining depth from the casing collar locator. Based on the known estimated optimum working ranges for ICD shifting and having access to real-time downhole data, the operator could decide that required force was transmitted to BHA. This bring about saving job time while finding sleeves, efficient open and close of ICD via applying required Weight on Bit (WOB) and even providing a mean to identify ICD that had debris accumulation. The experience acquired using this method in the successful operation in Saudi Arabia yielded recommendations for future similar operations.

A comparison of select trigger algorithms for automated global seismic phase and event detection

1998 ◽  
Vol 88 (1) ◽  
pp. 95-106 ◽  
Author(s):  
Mitchell Withers ◽  
Richard Aster ◽  
Christopher Young ◽  
Judy Beiriger ◽  
Mark Harris ◽  
...  
Keyword(s):  
Real Time ◽  
Data Streams ◽  
Event Detection ◽  
Spectral Characteristics ◽  
Digital Data ◽  
Robust Detection ◽  
Location System ◽  
Global Correlation ◽  
Seismic Coda ◽  
Wide Range

Abstract Digital algorithms for robust detection of phase arrivals in the presence of stationary and nonstationary noise have a long history in seismology and have been exploited primarily to reduce the amount of data recorded by data logging systems to manageable levels. In the present era of inexpensive digital storage, however, such algorithms are increasingly being used to flag signal segments in continuously recorded digital data streams for subsequent processing by automatic and/or expert interpretation systems. In the course of our development of an automated, near-real-time, waveform correlation event-detection and location system (WCEDS), we have surveyed the abilities of such algorithms to enhance seismic phase arrivals in teleseismic data streams. Specifically, we have considered envelopes generated by energy transient (STA/LTA), Z-statistic, frequency transient, and polarization algorithms. The WCEDS system requires a set of input data streams that have a smooth, low-amplitude response to background noise and seismic coda and that contain peaks at times corresponding to phase arrivals. The algorithm used to generate these input streams from raw seismograms must perform well under a wide range of source, path, receiver, and noise scenarios. Present computational capabilities allow the application of considerably more robust algorithms than have been historically used in real time. However, highly complex calculations can still be computationally prohibitive for current workstations when the number of data streams become large. While no algorithm was clearly optimal under all source, receiver, path, and noise conditions tested, an STA/LTA algorithm incorporating adaptive window lengths controlled by nonstationary seismogram spectral characteristics was found to provide an output that best met the requirements of a global correlation-based event-detection and location system.

An Efficient Smartphone Assisted Indoor Localization with Tracking Approach using Glowworm Swarm Optimization Algorithm

2021 ◽  
pp. 101-107
Author(s):  
Mohammad Alshehri ◽  
Keyword(s):  
Real Time ◽  
Indoor Localization ◽  
Initial Position ◽  
Swarm Optimization ◽  
The Real ◽  
Assisted Navigation ◽  
Glowworm Swarm Optimization ◽  
Tracking Process ◽  
Wide Range ◽  
Localization And Tracking

Presently, a precise localization and tracking process becomes significant to enable smartphone-assisted navigation to maximize accuracy in the real-time environment. Fingerprint-based localization is the commonly available model for accomplishing effective outcomes. With this motivation, this study focuses on designing efficient smartphone-assisted indoor localization and tracking models using the glowworm swarm optimization (ILT-GSO) algorithm. The ILT-GSO algorithm involves creating a GSO algorithm based on the light-emissive characteristics of glowworms to determine the location. In addition, the Kalman filter is applied to mitigate the estimation process and update the initial position of the glowworms. A wide range of experiments was carried out, and the results are investigated in terms of distinct evaluation metrics. The simulation outcome demonstrated considerable enhancement in the real-time environment and reduced the computational complexity. The ILT-GSO algorithm has resulted in an increased localization performance with minimal error over the recent techniques.

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