Real-time Gauge Research Articles

End-to-End Solution for Analog Gauge Monitoring Using Computer Vision in an IoT Platform.

The emergence of Industry 4.0 and 5.0 technologies has enabled the digital transformation of various processes and the integration of sensors with the internet. Despite these strides, many industrial sectors still rely on visual inspection of physical processes, especially those employing analog gauges. This method of monitoring introduces the risk of human errors and inefficiencies. Automating these processes has the potential, not only to boost productivity for companies, but also potentially reduce risks for workers. Therefore, this paper proposes an end-to-end solution to digitize analog gauges and monitor them using computer vision through integrating them into an IoT architecture, to tackle these problems. Our prototype device has been designed to capture images of gauges and transmit them to a remote server, where computer vision algorithms analyze the images and obtain gauge readings. These algorithms achieved adequate robustness and accuracy for industrial environments, with an average relative error of 0.95%. In addition, the gauge data were seamlessly integrated into an IoT platform leveraging computer vision and cloud computing technologies. This integration empowers users to create custom dashboards for real-time gauge monitoring, while also enabling them to set thresholds, alarms, and warnings, as needed. The proposed solution was tested and validated in a real-world industrial scenario, demonstrating the solution's potential to be implemented in a large-scale setting to serve workers, reduce costs, and increase productivity.

Stabilizing complex Langevin for real-time gauge theories with an anisotropic kernel

The complex Langevin (CL) method is a promising approach to overcome the sign problem that occurs in real-time formulations of quantum field theories. Using the Schwinger-Keldysh formalism, we study SU(Nc) gauge theories with CL. We observe that current stabilization techniques are insufficient to obtain correct results. Therefore, we revise the discretization of the CL equations on complex time contours, find a time reflection symmetric formulation and introduce a novel anisotropic kernel that enables CL simulations on discretized complex time paths. Applying it to SU(2) Yang-Mills theory in 3+1 dimensions, we obtain unprecedentedly stable results that we validate using additional observables and that can be systematically improved. For the first time, we are able to simulate non-Abelian gauge theory on time contours whose real-time extent exceeds its inverse temperature. Thus, our approach may pave the way towards an ab-initio real-time framework of QCD in and out of equilibrium with a potentially large impact on the phenomenology of heavy-ion collisions.

Real-Time Gauging of the Gelling Maturity of Duck Eggs Pickled in Strong Alkaline Solutions.

Although many ultraviolet-visible-near-infrared transmission spectroscopy techniques have been applied to chicken egg studies, such techniques are not suitable for duck eggs because duck eggshells are much thicker than chicken eggshells. In this study, a high-transmission spectrometer using an equilateral prism as a dispersive element and a flash lamp as a light source was constructed to nondestructively detect the transmission spectrum of duck eggs and monitor the pickling of eggs. The evolution of egg transmittance was highly correlated with the albumen during pickling. The transmittance exponentially decays with time during this period, and the decay rate is related to the pickling rate. The colors of the albumen and yolk remain almost unchanged in the first stage. A multiple linear regression analysis model that realizes a one-to-one association between the days of pickling and the transmission spectra was constructed to determine the pickling duration in the second stage. The coefficient of determination reached 0.88 for a single variable, wavelength, at 590 nm. This method can monitor the maturity of pickled eggs in real time and does not require the evolution of light transmittance.

Real-time lattice gauge theory actions: Unitarity, convergence, and path integral contour deformations

The Wilson action for Euclidean lattice gauge theory defines a positive-definite transfer matrix that corresponds to a unitary lattice gauge theory time-evolution operator if analytically continued to real time. Hoshina, Fujii, and Kikukawa (HFK) recently pointed out that applying the Wilson action discretization to continuum real-time gauge theory does not lead to this, or any other, unitary theory and proposed an alternate real-time lattice gauge theory action that does result in a unitary real-time transfer matrix. The character expansion defining the HFK action is divergent, and in this work we apply a path integral contour deformation to obtain a convergent representation for $U(1)$ HFK path integrals suitable for numerical Monte Carlo calculations. We also introduce a class of real-time lattice gauge theory actions based on analytic continuation of the Euclidean heat-kernel action. Similar divergent sums are involved in defining these actions, but for one action in this class this divergence takes a particularly simple form, allowing construction of a path integral contour deformation that provides absolutely convergent representations for $U(1)$ and $SU(N)$ real-time lattice gauge theory path integrals. We perform proof-of-principle Monte Carlo calculations of real-time $U(1)$ and $SU(3)$ lattice gauge theory and verify that exact results for unitary time evolution of static quark-antiquark pairs in ($1+1$)D are reproduced.

Real-time bias adjustment for satellite-based precipitation estimates over Mainland China

An improved cumulative distribution function (CDF)-based approach to reduce the systematic biases of multi-satellite precipitation estimates in real time is proposed and verified over Mainland China. Efforts are primarily focused on establishing the bias-adjusting model by adopting the CDF based on a Self-adaptive Moving Window (CSMW), which systematically integrates the China Gauge-based Daily Precipitation Analysis (CGDPA) into the real-time TRMM Multisatellite Precipitation Analysis (TMPA-RT). In our modelling experiments, the first 9-yr (2008–2016) precipitation data pairs were used to calibrate the CSMW model and establish a satellite-gauge relationship, which was then applied to the last 3 years of 2017–2019 as validation. Assessment results during the independent validation period show that the CSMW approach can significantly reduce the systematic positive bias of original TMPA-RT precipitation estimates in that the relative bias (RB) during the validation period decreases from 16.01% before adjustments to −0.29%, and the root-mean-square error (RMSE) also has a dramatic drop of 13%. The error component analysis indicates that the substantial improvement is mainly manifested in the hit events (observed rain was correctly detected by satellite) but it failed to reduce the miss bias (observed rain was not detected by satellite). This arises because a majority of missed precipitation is drizzle and falls below the rain/no-rain discriminant threshold, which is normally excluded from the CSMW algorithm. Additionally, the CSMW approach seems to have significantly improved the TMPA-RT estimates at the medium-high rain rates (>8 mm/day), but it also has a limitation in enhancing the correlation coefficient between satellite retrievals and ground observations. The major advantage of this approach is its applicability when real-time gauge data are not available, which could further facilitate the expansion of satellite-based precipitation estimates for real-time natural hazards forecasting.

Remote Monitoring Digitizes Asset-Integrity Management

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.

A Dynamic Approach to Quantitative Precipitation Estimation Using Multiradar Multigauge Network

Effective utilization of the changing precipitation microphysics in real-time radar quantitative precipitation estimation (QPE) is challenging, which requires dynamic adjustment of the radar reflectivity (Z) and rain rate (R) relations. This article develops and demonstrates two dynamic radar rainfall approaches using 16 Doppler weather radars and 4579 surface rain gauges deployed over the Eastern Jiang Huai River Basin (EJRB) in China. Both approaches are derived based on the radar-gauge feedback mechanism. Although the Z-R relations in both approaches are dynamically adjusted within a precipitation system, one is using a single global optimum (SGO) Z-R relation, while the other is using different Z-R relations for different storm cells identified by a storm cell identification and tracking (SCIT) algorithm. Four precipitation events featured by different rainfall characteristics are investigated to evaluate the performances of various QPE methodologies. In addition, the shortterm vertical profile of reflectivity (VPR) clusters is extensively analyzed to resolve the storm-scale characteristics of different storm cells. The evaluation results based on independent gauge observations show that both rainfall approaches with dynamic Z-R relations perform much better than the fixed Z-R relations. The adaptive approach incorporating the SCIT algorithm and real-time gauge measurements has the best performance since it can better capture the spatial variability and evolution of precipitation.

Attenuating Neurogenic Sympathetic Hyperreflexia Robustly Improves Antibacterial Immunity After Chronic Spinal Cord Injury.

Spinal cord injury (SCI) disrupts critical physiological systems, including the cardiovascular and immune system. Plasticity of spinal circuits below the injury results in abnormal, heightened sympathetic responses, such as extreme, sudden hypertension that hallmarks life-threatening autonomic dysreflexia. Moreover, such sympathetic hyperreflexia detrimentally impacts other effector organs, including the spleen, resulting in spinal cord injury-induced immunodeficiency. Consequently, infection is a leading cause of mortality after SCI. Unfortunately, there are no current treatments that prophylactically limit sympathetic hyperreflexia to prevent subsequent effector organ dysfunction. The cytokine soluble tumor necrosis factor α (sTNFα) is upregulated in the CNS within minutes after SCI and remains elevated. Here, we report that commencing intrathecal administration of XPro1595, an inhibitor of sTNFα, at a clinically feasible, postinjury time point (i.e., 3 d after complete SCI) sufficiently diminishes maladaptive plasticity within the spinal sympathetic reflex circuit. This results in less severe autonomic dysreflexia, a real-time gauge of sympathetic hyperreflexia, for months postinjury. Remarkably, delayed delivery of the sTNFα inhibitor prevents sympathetic hyperreflexia-associated splenic atrophy and loss of leukocytes to dramatically improve the endogenous ability of chronic SCI rats to fight off pneumonia, a common cause of hospitalization after injury. The improved immune function with XPro1595 correlates with less noradrenergic fiber sprouting and normalized norepinephrine levels in the spleen, indicating that heightened, central sTNFα signaling drives peripheral, norepinephrine-mediated organ dysfunction, a novel mechanism of action. Thus, our preclinical study supports intrathecally targeting sTNFα as a viable strategy to broadly attenuate sympathetic dysregulation, thereby improving cardiovascular regulation and immunity long after SCI.SIGNIFICANCE STATEMENT Spinal cord injury (SCI) significantly disrupts immunity, thus increasing susceptibility to infection, a leading cause of morbidity in those living with SCI. Here, we report that commencing intrathecal administration of an inhibitor of the proinflammatory cytokine soluble tumor necrosis factor α days after an injury sufficiently diminishes autonomic dysreflexia, a real time gauge of sympathetic hyperreflexia, to prevent associated splenic atrophy. This dramatically improves the endogenous ability of chronically injured rats to fight off pneumonia, a common cause of hospitalization. This preclinical study could have a significant impact for broadly improving quality of life of SCI individuals.

Celeris Base: An interactive and immersive Boussinesq-type nearshore wave simulation software

We introduce our interactive and immersive coastal wave simulation software, Celeris Base, which is the successor to Celeris Advent. Celeris Base is an open source software developed in the Unity3D game engine and in C# language. It supports an interactive environment and allows users to view the simulations in a virtual reality headset. Celeris Base solves the same equations as Celeris Advent, the extended Boussinesq equations, using our hybrid finite volume–finite difference method. These equations are solved on the GPU using compute shaders, written in HLSL. Celeris Base has several new features such as 360°video capturing, geographic map overlays, built-in real-time gauge plotters, etc. It also improves the implementation of the sponge layer boundary condition by introducing new damping equations. Celeris Base is designed and implemented using the best software engineering practices in the hope that it will be a base for further developments of the Celeris software series by researchers around the globe. We validate Celeris Base against experimental results in this paper. Program summaryProgram Title: Celeris BaseProgram Files doi:http://dx.doi.org/10.17632/jdx7tddcxz.1Licensing provisions: MIT LicenseProgramming language: C#, HLSLNature of problem: Celeris Advent enabled researchers and engineers for the first time to simulate nearshore waves with a Boussinesq-type model, faster than real-time and in an interactive environment. However, its development platform and implementation complexity hindered researchers from developing it further and made adding new features to the software a daunting task. The software used graphics shaders to solve scientific equations which could be confusing for many. The visualization environment was wired from scratch which made it very difficult to add features such as virtual reality.Solution method: A new software is developed completely from scratch following Celeris Advent, called Celeris Base. This software uses the same hybrid finite volume–finite difference scheme to solve the extended Boussinesq equations, but using a variant of shaders called compute shaders, removing possible barriers for other researchers to understand the code and develop it further. The software is developed in Unity3D, a popular game engine with a large and helpful community as well as thousands of ready to use plugins. Celeris Base is equipped with virtual reality and is the first nearshore simulation software to provide this feature.

Implicit schemes for real-time lattice gauge theory

We develop new gauge-covariant implicit numerical schemes for classical real-time lattice gauge theory. A new semi-implicit scheme is used to cure a numerical instability encountered in three-dimensional classical Yang-Mills simulations of heavy-ion collisions by allowing for wave propagation along one lattice direction free of numerical dispersion. We show that the scheme is gauge covariant and that the Gauss constraint is conserved even for large time steps.

Reconstructing Flood Inundation Probability by Enhancing Near Real-Time Imagery With Real-Time Gauges and Tweets

Flood inundation probability is critical for situation awareness, flood mitigation, emergency response, and postevent damage assessment. Current flood inundation mapping approaches can be categorized into real-time (RT) and near-RT (NRT) processes based on the timing of data acquisition. However, the intrinsic limitations of each category largely hamper their applications for flood mapping. Taking the 2015 South Carolina flood in downtown Columbia as a case study, this paper proposes a flood inundation reconstruction model by enhancing the NRT normalized difference water index (NDWI) derived from remote sensing imagery with the RT data including stream gauge readings and social media (tweets). Splitting into three modules: water height module, global enhancement module, and local enhancement module, the proposed model first incorporates the gauge readings and the NDWI image to reconstruct a macroscale flood probability layer, which is then locally enhanced using the verified flood-related tweets. The final output of the model matches well with the U.S. Geological Survey inundation map and its surveyed high-water marks. Results suggest that by enhancing NRT imagery with RT data sources, the proposed flood inundation probability reconstruction model renders a more robust, spatially enhanced flood probability index for emergency responders to quickly identify areas in need of urgent attention.

Real-Time Gauge Wheel Load Variability of a Row-Crop Planter During Field Operation

Abstract. Planter downforce control allows row units to maintain a target gauge wheel load (GWL) across a range of soil resistance within a field. Downforce control is typically set for a target seed depth and can be implemented either as fixed or by automatic or active control to attain the desired GWL. Recent advances allow for the control of individual row units into sections for improved GWL application. However, little knowledge exists on the spatial variability of GWL, row-to-row GWL variability, and on the recommended GWL control requirements on planters operating in actual field conditions. Therefore, the objectives of this study were to (1) quantify real-time GWL variability across individual row units within a 12-row crop planter programmed to implement a constant downforce control during field operations; (2) evaluate gauge wheel load range (GWLR) across individual row units and within 2-row, 3-row, or 4-row control sections to determine the optimal downforce control section size; and (3) assess the impact of soil texture and soil compaction due to tire tracks on GWL variability. To address these objectives, a 12-row crop planter equipped with hydraulic downforce control was used to plant three fields. The planter was set to plant corn at 5.2 and 5.7 cm depths with fixed target GWL set at 334 ±223 N (111 to 557 N) and GWLR set at 0 to 883 N. A data acquisition system collected real-time GPS, planting speed, GWL, hydraulic pressure, and planter toolbar height data at 10 Hz. Real-time GWL data of individual row units were analyzed to determine the GWL distribution within or outside the set target GWL. Moreover, GWLR was measured in individual row units and across varying control section sizes. Soil electrical conductivity (EC) was measured using a Veris mobile sensor platform. Soil EC was used in defining zones of low, medium, and high textured soil. Results show that GWL was within the target range of 111 to 557 N at 33% of the total planting time across the three fields, and GWLR was within 0 to 441 N at 9% of the total planting time. Results also indicate that a 2-row, 3-row, and 4-row control section could provide GWLR within 0 to 441 N at 76%, 46%, and 28% of the total planting time, respectively. These findings suggest the need for automatic downforce systems with fewer row units per control section to maintain target GWL within an acceptable range for all row units. Regression analyses indicate that soil texture is a significant variable that can influence real-time GWL. Furthermore, compacted soil due to tractor tires contributed to significantly lower GWL. Our data suggest the need for active downforce control to achieve improved GWL uniformity under varying field-operating conditions. Keywords: Gauge wheel load, Planter downforce, Precision planters, Seeding depth, Variability.

Macroeconomic and Political Uncertainty and Cross Sectional Return Dispersion Around the World

Cross sectional return dispersion seems a simple, good, real time gauge of uncertainty. Internationally, cross-sectional return dispersion correlates strongly with all sorts of measures of macroeconomic and political uncertainty like, (global) recessions, international political crises, country risk, and uncertainty related to government policies. While we find that return dispersion and implied volatility are correlated, surprisingly only return dispersion relates to the cross section of returns. Return dispersion seems to capture political uncertainty better. Implied volatility seems linked stronger to economic uncertainty.

Design and Development of OBD-II Compliant Driver Information System

Background/Objectives: On-Board Diagnostics, or OBD, in a vehicle connection, is a term alluding to a vehicle's logical toward oneself and reporting ability. OBD systems give the vehicle proprietor or a repair expert access to condition of origin data for different vehicle sub-systems. Methods/Statistical Analysis: The driver data framework (DIS) is connected in a vehicle through OBD-II connector. Initially, live information undertaking that gives real time gauges reading. The live information is constrained to show an ambient temperature, Throttle position, Intake manifold absolute pressure, MAF air flow rate, calculated engine load value, intake air temperature, Engine coolant temperature, RPM and vehicle speed (km/h). Second assignment is DTC filtering framework that offers diagnostic trouble codes. Findings: The point of this venture is to get a completely useful Programmable System on Chip (PSoC) platform working with observing live data monitoring and DTCs corresponds with all present day vehicles. Correspondence to and from the ECU will be done utilizing the On-Board Diagnostics two (OBD-II) standard. The correspondence with the ECU must be taken care of utilizing a surveying sort system as information programmed overhauling of information from the ECU isn't possible sporadically. Rather a cyclic process or string will need to run ceaselessly to do a question to the ECU took after by the perusing of the answer. The product will need to work with the returned hexadecimal information in a manner that gives the client or driver valuable information. Conclusion/Improvements: Driver Information System (DIS) helps effective and efficient use of vehicles and can assist a relatively inexperienced drive to shift to proper gears or proper acceleration according to the load on the engine and there by achieve better fuel economy and better emission performance.

Exploring Return Dynamics via Corridor Implied Volatility

Some fundamental questions regarding equity-index return dynamics are difficult to address due to the latent character of spot volatility. We exploit tick-by-tick option quotes to compute a novel Corridor Volatility index which may serve as an observable proxy for short-term volatility. Exploiting this index, we find that equity-index volatility jumps are common, symmetrically distributed, and cojump with the underlying returns. Moreover, the return-volatility asymmetry is more pronounced than is generally recognized and is in force for both diffusive and jump innovations in volatility. Finally, the index performs admirably during turbulent market conditions, constituting a useful real-time gauge of market stress.

Coherent Model-Free Implied Volatility: A Corridor Fix for High-Frequency VIX

A number of fundamental questions regarding the equity-index return dynamics are difficult to address due to the latent character of spot volatility. We exploit tick-by-tick option quotes to compute a novel Corridor Implied Volatility,'' or CX, index which may serve as an observable proxy for short-term volatility. Exploiting this index, we obtain striking new empirical findings. In particular, equity-index volatility jumps are common and they are symmetrically distributed and co-jump with the underlying returns. Moreover, the return-volatility asymmetry, or leverage effect, is more pronounced than generally recognized and is in force for both diffusive and jump innovations in volatility. Finally, the CX index performs admirably during turbulent market conditions so it constitutes a useful real-time gauge of market stress.

Probability prediction model for landslide occurrences in Xi’an, Shaanxi Province, China

Landslides are increasing since the 1980s in Xi’an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall (IR) and antecedent effective rainfall (AER). Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; “A” region is safe, “B” region is on watch alert, “C” region is on warning alert and “D” region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi’an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi’an region.

Forecasting Wave Amplitudes after the Arrival of a Tsunami

The destructive Pacific Ocean tsunami generated off the east coast of Honshu, Japan, on 11 March 2011 prompted the West Coast and Alaska Tsunami Warning Center (WCATWC) to issue a tsunami warning and advisory for the coastal regions of Alaska, British Columbia, Washington, Oregon, and California. Estimating the length of time the warning or advisory would remain in effect proved difficult. To address this problem, the WCATWC developed a technique to estimate the amplitude decay of a tsunami recorded at tide stations within the Warning Center’s Area of Responsibly (AOR). At many sites along the West Coast of North America, the tsunami wave amplitudes will decay exponentially following the arrival of the maximum wave (Mofjeld et al., Nat Hazards 22:71–89, 2000). To estimate the time it will take before wave amplitudes drop to safe levels, the real-time tide gauge data are filtered to remove the effects of tidal variations. The analytic envelope is computed and a 2 h sequence of amplitude values following the tsunami peak is used to obtain a least squares fit to an exponential function. This yields a decay curve which is then combined with an average West Coast decay function to provide an initial tsunami amplitude-duration forecast. This information may then be provided to emergency managers to assist with response planning.

Well-Testing Operations in High-Temperature Environments - Experiences and Best Practices

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 148575, ’Challenging Well-Testing Operations in High-Temperature Environments - Worldwide Experiences and Best Practices Learned,’ by Alejandro Salguero, SPE, Edgar Almanza, and Josmar Haddad, SPE, Halliburton, prepared for the 2011 SPE/IADC Middle East Drilling Technology Conference and Exhibition, Muscat, Oman, 24-26 October. The paper has not been peer reviewed. High-temperature (HT) wells are classified as those with bottomhole temperatures in excess of 300°F. New technologies and advances in the industry (e.g., gauges, downhole equipment, and samplers) have been applied to improve decision-making capabilities and to increase well-testing-evaluation success, even in extreme and challenging environments. These enhancements enable improved economics and operational efficiency along with better safety conditions for the involved personnel and lower environmental risk during testing operations. Introduction Well testing is a reliable, dynamic method of retrieving and collecting a variety of information from the reservoir, including permeability, formation damage, bottomhole pressure and temperature, fluid samples, and production quantification. The methods and equipment used to collect these data have evolved as exploration has moved into more-demanding and -challenging environments. In recent years, high-pressure/high-temperature (HP/HT) wells have become more common, and they required new techniques that support the environmental challenges. Proper planning and personnel and qualified equipment are key to achieve successful well-test results, especially considering that well and reservoir conditions can change easily from one region to another, adding challenges to the evaluation operation. HT prospects are defined as wells having bottomhole temperatures in excess of 300°F, and extreme HT wells are prospects having bottomhole temperatures of 350 to 400°F. The chart in Fig. 1 depicts designations for each pressure and temperature definition. Most HT cases have required the use of a deep-well simulator to test and qualify/certify equipment for the expected well-test conditions. The complete paper details three cases of testing wells with temperatures ranging from 340 to 430°F. These cases were carried out in different geographical locations. These wells were chosen because different bottomhole configurations of full-scale downhole assemblies were used. It is important to mention that special tools and equipment are available to perform operations under extreme conditions (e.g., 450°F and 20,000 psi). Currently, electronic memory gauges used in drillstem-test (DST) equipment are designed and tested to work in conditions of 400°F and 30,000 psia. Real-time gauges are available that have been tested to 350°F. However, when more-challenging conditions are encountered, mechanical pressure and temperature gauges must be used.

A Successful Application of Fiber-Optic-Enabled Coiled Tubing With Distributed-Temperature Sensing Along With Pressures To Diagnose Production Decline in an Offshore Oil Well

Summary In this paper, we present a field example where pressure and distributed-temperature measurements enabled understanding of reservoir characteristics and fluid movement causing production hindrance in an offshore horizontal well. The field example has a horizontal well in the South China Sea that was completed as an openhole monobore oil producer using a slotted liner. The well began production with an initial oil rate of 1,800 B/D. Oil production quickly dropped to 1,000 B/D and gradually declined to 200 B/D. During this period, the gas/oil ratio (GOR) steadily increased from 200 scf/bbl to 2,200 scf/bbl. To arrest production decline, a chemical treatment was conducted to remove suspected emulsions and polymers assumed to have been deposited during drilling. Immediate post-treatment production increased to 3,700 B/D, but dropped dramatically and stabilized at pretreatment rates soon after. Formation of emulsions and asphaltenes were believed to be the cause of the production decline. However, with inadequate information, the diagnosis was inconclusive. Consequently, another chemical treatment was conducted and this time, a fiber-optic-enabled coiled-tubing (CT) string along with real-time bottomhole-pressure and temperature gauges were used to acquire distributed temperatures and pressures of the entire horizontal section of the wellbore. Results of the pressure survey revealed that the well was receiving insufficient pressure support from the water injector, which was causing gas-cap expansion. The distributed-temperature survey indicated excessive gas production from the toe of the horizontal section as a result of this expansion, thus limiting liquid production. The combination of gas rates with oil and water production has also created tight emulsions, further hindering production performance. It was concluded that the high gas production from the toe could not be selectively shutoff or controlled in the horizontal openhole slotted-liner completion to perform an effective stimulation program and treat the tight viscous emulsions.