Surface pH Measurement during CO2 Corrosion by an IrOx pH Probe

2016 ◽  
Vol 1133 ◽  
pp. 381-385
Author(s):  
Saeid Kakooei ◽  
Mokhtar Che Ismail ◽  
Bambang Ari-Wahjoedi

CO2 corrosion comprises the majority of material damage, which leads to shutdown in petroleum industries. This phenomenon depends on parameters such as pH and temperature. Monitoring and recording these parameters help industries minimize waste in terms of time and financial resources. The insufficiency of tools for this purpose is noticeable. This study proposed an potentiometric IrO2–pH microelectrode design in conjuction with a Ag/AgCl refrence electrode for real-time corrosion monitoring that can be used in various industries. Electrodeposition approach was used in the fabrication of a pH sensor. Electrochemical experiments were conducted to characterize the IrO2–pH sensor as well as monitor the pH on a metal surface in conjunction with the fabrication of a pH microelectrode-designed system. Results show that the proposed pH sensor design can be used for real-time corrosion monitoring by surface pH measurement.

Molecules ◽  
2021 ◽  
Vol 26 (12) ◽  
pp. 3682
Author(s):  
Katarína Vizárová ◽  
Izabela Vajová ◽  
Naďa Krivoňáková ◽  
Radko Tiňo ◽  
Zdenko Takáč ◽  
...  

The surface pH is a critical factor in the quality and longevity of materials and products. Traditional fast colorimetric pH detection-based tests such as water quality control or pregnancy tests, when results are determined by the naked eye, cannot provide quantitative values. Using standard pH papers, paper-printed comparison charts, or colorimetric microfluidic paper-based analytical devices is not suitable for such technological applications and quality management systems (QMSs) where the particular tested material should contain a suitable indicator in situ, in its structure, either before or after the process, the technology or the apparatus that are being tested. This paper describes a method based on the combination of impregnation of a tested material with a pH indicator in situ, its exposure to a process of technology whose impact on pH value is to be tested, colorimetric pH measurement, and approximation of pH value using derived pH characteristic parameters (pH-CPs) based on CIE orthogonal and cylindrical color variables. The hypotheses were experimentally verified using the methyl red pH indicator, impregnating the acid lignin-containing paper, and preparing a calibration sample set with pH in the range 4 to 12 using controlled alkalization. Based on the performed measurements and statistical evaluation, it can be concluded that the best pH-CPs with the highest regression parameters for pH are √∆E, ln (a),√∆H (ab), a/L, h/b and ln (b/a). The experimental results show that the presented method allows a good estimation of pH detection of the material surfaces.


Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 25
Author(s):  
Shijie Deng ◽  
Alan P. Morrison ◽  
Yong Guo ◽  
Chuanxin Teng ◽  
Ming Chen ◽  
...  

The design and implementation of a real-time breakdown voltage and on-chip temperature monitoring system for single photon avalanche diodes (SPADs) is described in this work. In the system, an on-chip shaded (active area of the detector covered by a metal layer) SPAD is used to provide a dark count rate for the breakdown voltage and temperature calculation. A bias circuit was designed to provide a bias voltage scanning for the shaded SPAD. A microcontroller records the pulses from the anode of the shaded SPAD and calculates its real-time dark count rate. An algorithm was developed for the microcontroller to calculate the SPAD’s breakdown voltage and the on-chip temperature in real time. Experimental results show that the system is capable of measuring the SPAD’s breakdown voltage with a mismatch of less than 1.2%. Results also show that the system can provide real-time on-chip temperature monitoring for the range of −10 to 50 °C with errors of less than 1.7 °C. The system proposed can be used for the real-time SPAD’s breakdown voltage and temperature estimation for dual-SPADs or SPAD arrays chip where identical detectors are fabricated on the same chip and one or more dummy SPADs are shaded. With the breakdown voltage and the on-chip temperature monitoring, intelligent control logic can be developed to optimize the performance of the SPAD-based photon counting system by adjusting the parameters such as excess bias voltage and dead-time. This is particularly useful for SPAD photon counting systems used in complex working environments such as the applications in 3D LIDAR imaging for geodesy, geology, geomorphology, forestry, atmospheric physics and autonomous vehicles.


2005 ◽  
Author(s):  
B. Raghuraman ◽  
M. O'Keefe ◽  
K.O. Eriksen ◽  
L.A. Tau ◽  
O. Vikane ◽  
...  

2021 ◽  
Author(s):  
Klemens Katterbauer ◽  
Waleed Dokhon ◽  
Fahmi Aulia ◽  
Mohanad Fahmi

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.


2021 ◽  
Vol 73 (01) ◽  
pp. 65-66
Author(s):  
Chris Carpenter

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 197168, “Digitalize Asset-Integrity Management by Remote Monitoring,” by Mohamed Sahid, ADNOC, prepared for the 2019 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, 11-14 November. The paper has not been peer reviewed. Monitoring of corrosion in process pipelines has always been of paramount importance in ensuring plant-asset integrity. Similarly, steam traps play an important role in ensuring steam quality and, thus, the integrity of critical assets in the plant. The complete paper discusses these two aspects of monitoring asset integrity - real-time corrosion monitoring and real-time steam-trap monitoring - as implemented by the operator. The authors highlight the importance of digitization by means of implementing wireless technology and making data available in remote work stations in real time. Real-Time Corrosion-Monitoring System Corrosion coupons and electrical resistance probes are among the most-tried and -tested methods to monitor corrosion, but the authors detail shortcomings of these systems, focusing their efforts on the option of using nonintrusive ultrasonic sensors for corrosion monitoring. Fixed ultrasonic thickness (UT) monitoring systems measure a localized thickness of vessel wall or pipe through the use of sound waves. They are the fastest method to measure wall thickness and wall loss reliably. The wall thickness is calculated from the reflection of the ultrasonic signal at both external and internal surfaces. UT systems normally include a transducer and a pulser/receiver. The type of transducer used for this application is the ultrasonic transducer, which can be either piezoelectric or variable-capacitive. The pulser generates short electric pulses of energy at a constant rate, which are converted by the transducer into short, high-frequency ultrasonic sound pulses. These pulses are then directed into the material. Any discontinuation or impurity in the path of the ultrasonic sound wave will be reflected and received by the transducer, transformed into an electric signal, and amplified by the receiver to be projected onto the display (in the case of portable UT instruments). Depending on the intensity shown on the display, information about the impurity or discontinuity, such as size, orientation, and location, can be derived accurately. The shortcomings of using portable UT sensors have been overcome by the introduction of permanent UT sensors, which provide wall-thickness measurement continuously at one location in real time. Because these sensors remain fixed at one location for years, it is possible to analyze corrosion at a single point over time, thus detecting early corrosion onset. Real-Time UT Gauging. The operator installed the real-time corrosion-monitoring system in its offshore associated gas (OAG) unit. A UK-based vendor provided UT sensors along with data-management and -viewing software to support data interpretation. Twenty locations were identified in various plants of the OAG unit on the basis of criticality and previously recorded corrosion levels.


2019 ◽  
Author(s):  
Amit Kumar ◽  
Tareq Al Daghar ◽  
Ali Al Shehhi ◽  
Brendon Keinath ◽  
Mohan Kulkarni ◽  
...  

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