Intelligent Operating Envelope Integrated with Automated Well Models Improves Asset Wide PCP Surveillance and Optimization

2021 ◽  
Author(s):  
Mohammed Al Sawafi ◽  
Antonio Andrade ◽  
Nitish Kumar ◽  
Rahul Gala ◽  
Eduardo Marin ◽  
...  
Keyword(s):  
Real Time ◽  
Optimum Operating ◽  
Well Performance ◽  
Optimum Operating Condition ◽  
Visualization System ◽  
Well Design ◽  
Well Model ◽  
Operational Activities ◽  
Petroleum Development ◽  
Well Models

Abstract Petroleum Development Oman (PDO) has been a pioneer in improving Well management processes utilizing its valuable human resources, continuous improvement and digitalization. Managing several PCP wells through Exception Based Surveillance (EBS) methodology had already improved PCP surveillance and optimization across assets. The key to trigger EBS was to keep Operating Envelope (OE), Design Limits updated in Well Management Visualization System (WMVS) after every change in operating speed (RPM), workover and new completion. The sustainable solution was required for automatic update of OEs, having well inflow potential and oil gain opportunities available for quicker optimization decisions for further improvements. PDO has completed a project automating PCP well modeling process where models are built and sustained automatically in Well Management System (WMS) for all active PCP wells, with huge impact on day-to-day operational activities. The paper discusses utilization of physics based well models from WMS to automatically update OE, identify oil gain potential daily and enable real time PCP performance visualization in WMVS. The integration of WMS and WMVS was completed to share data between two systems and automatically update well's OE daily. A tuned well model from WMS was utilized to provide well performance data and sensitivity analysis results for various RPMs. Among the various data obtained from WMS, live OE of torque and fluid above pump (FAP) for various speeds, operating limits, design limits, locked in potential (LIP) for optimization and pump upsize were utilized to process PCP well EBS and create live OE visualization. The visualization is created on a torque-speed chart where a live OE and FAP can be observed in provided picture with current RPM and torque with optimum operating condition. The project is completed after conducting successful change management across PDO assets and after thorough analysis of implementation following benefits were observed: 5% net gain of total PCP production is being executed with zero CAPEX using LIP reports. 50% of engineer's time was saved by updating OEs in WMVS automatically, reduction of false EBS and EBS rationalization. 200% improvement in PCP well performance diagnostics capabilities of Engineers. 15% CAPEX free optimization and pump upsize cases were identified based on well inflow potential. 100% visibility to PCP well's performance was achieved using well model. The visualization has supported engineers monitoring well performance in real time and easily identifying ongoing changes in well and pump performance. PCP well models have supported engineers in new PCP well design and pump upsize. The current efforts in utilizing real time well models, inferred production, automating processes to update OE is one more step toward Digitalization of PCP Surveillance and optimization and to achieve self well optimization for further improving operational efficiency.

Maximising Asset Value through Implementation of Dynamic Well Operating Envelop

2021 ◽  
Author(s):  
Rafael Islamov ◽  
Eghbal Motaei ◽  
Bahrom Madon ◽  
Khairul Azhar Abu Bakar ◽  
Victor Hamdan ◽  
...  
Keyword(s):  
Real Time ◽  
Performance Monitoring ◽  
Oil And Gas ◽  
Operating Conditions ◽  
Well Performance ◽  
Time Dynamic ◽  
Well Model ◽  
Maximum Range ◽  
Facilities Design ◽  
Well Models

Abstract Dynamic Well Operating Envelop (WOE) allows to ensure that well is maintained and operated within design limits and operated in the safe, stable and profitable way. WOE covers the Well Integrity, Reservoir constraints and Facility limitations and visualizes them on well performance chart (Hamzat et al., 2013). Design and operating limits (such as upper and lower completion/facilities design pressures, sand failure, erosion limitations, reservoir management related limitations etc) are identified and translated into two-dimensional WOE (pressure vs. flowrate) to ensure maximum range of operating conditions that represents safe and reliable operation are covered. VLP/IPR performance curves were incorporated based on latest Validated Well Model. Optimum well operating window represents the maximum range of operating conditions within the Reservoir constraints assessed. By introducing actual Well Performance data the optimisation opportunities such as production/injection enhancement identified. During generating the Well Operating Envelops tremendous work being done to rectify challenges such as: most static data (i.e. design and reservoir limitations) are not digitized, unreliable real-time/dynamic data flow (i.e. FTHP, Oil/Gas rates etc), disintegrated and unreliable well Models and no solid workflows for Flow assurance. As a pre-requisite the workflows being developed to make data tidy i.e.ready and right, and Well Model inputs being integrated to build updated Well Models. Successful WOE prototype is generated for natural and artificially lifted Oil and Gas wells. Optimisation opportunities being identified (i.e. flowline pressure reduction, reservoir stimulation and bean-up) Proactive maintenance is made possible through dynamic WOE as a real time exceptional based surveillance (EBS) tool which is allowing Asset engineers to conduct the well performance monitoring, and maintain it within safe, stable and profitable window. Additionally, it allows to track all Production Enhancement jobs and seamless forecasting for new opportunities.

scholarly journals Swelling Elastomers and Tubular Expansion—Numerical Investigation

2021 ◽  
Author(s):  
Sayyad Zahid Qamar ◽  
Maaz Akhtar ◽  
Tasneem Pervez
Keyword(s):  
Performance Analysis ◽  
Numerical Investigation ◽  
Field Conditions ◽  
Well Performance ◽  
Well Design ◽  
Sealing Material ◽  
Zonal Isolation ◽  
Petroleum Development ◽  
Sealing Elements

Swell packers were initially used for repair of old and damaged wells, but they are now increasingly used for higher productivity and profitability through developments like slim well design and reduced-cement or cementless completions. Solid expandable tubular (SET) technology has gained popularity in the petroleum development industry as it can reduce well costs and improve well performance. A conical mandrel is pushed or pulled through a petroleum tubular, either hydraulically or mechanically, to expand it (in-situ) to the desired diameter. In SET applications such as water shutoff and zonal isolation, swelling elastomers are an obvious choice as a sealing material. For proper downhole deployment of swell packers in SET applications, it is important to have a good idea about their behavior under a given set of field conditions. Design and manufacturing of SET applications using swelling elastomers as sealing elements also needs some sort of seal performance analysis.

Into Mesh Lubrication of Spur Gears With Arbitrary Offset Oil Jet. Part 1: For Jet Velocity Less Than or Equal to Gear Velocity

1983 ◽  
Vol 105 (4) ◽  
pp. 713-718 ◽  
Author(s):  
L. S. Akin ◽  
D. P. Townsend
Keyword(s):  
Inclination Angle ◽  
Gear Tooth ◽  
Optimum Operating ◽  
Spur Gears ◽  
Optimum Operating Condition ◽  
Operating Condition ◽  
The Common ◽  
Jet Velocity ◽  
Oil Jet

An analysis was conducted for into mesh oil jet lubrication with an arbitrary offset and inclination angle from the pitch point for the case where the oil jet velocity is equal to or less than pitch line velocity. The analysis includes the case for the oil jet offset from the pitch point in the direction of the pinion and where the oil jet is inclined to intersect the common pitch point. Equations were developed for the minimum oil jet velocity required to impinge on the pinion or gear and the optimum oil jet velocity to obtain the maximum impingement depth. The optimum operating condition for best lubrication and cooling is provided when the oil jet velocity is equal to the gear pitch line velocity with both sides of the gear tooth cooled. When the jet velocity is reduced from pitch line velocity the drive side of the pinion and the unloaded side of the gear is cooled. When the jet velocity is much lower than the pitch line velocity the impingement depth is very small and may completely miss the pinion.

Thermoeconomic Approach and Optimization of a Solar Thermal Power Plant

2012 ◽  
Vol 232 ◽  
pp. 609-613
Author(s):  
Ali Baghernejad ◽  
Mahmood Yaghoubi
Keyword(s):  
Power Plant ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Production Costs ◽  
Solar Thermal ◽  
Optimum Operating ◽  
Production Plant ◽  
Optimum Operating Condition ◽  
Solar Thermal Power

In the present study, a specific and simple second law based exergoeconomic model with instant access to the production costs is introduced. The model is generalized for a case study of Shiraz solar thermal power plant with parabolic collectors for nominal power supply of 500 kW. Its applications include the evaluation of utility costs such as products or supplies of production plant, the energy costs between process operations of an energy converter such as production of an industry. Also attempt is made to minimize objective function including investment cost of the equipments and cost of exergy destruction for finding optimum operating condition for such plant.

Optimization of Fermentable Sugar Production from Pineapple Leaf Waste (Ananas comosus [L.] Merr) by Enzymatic Hydrolysis

2021 ◽  
Vol 18 (1) ◽  
pp. 73-80
Author(s):  
Yohanita Restu Widihastuty ◽  
Sutini Sutini ◽  
Aida Nur Ramadhani
Keyword(s):  
Enzymatic Hydrolysis ◽  
Complex Structure ◽  
Reducing Sugar ◽  
Sugar Yield ◽  
Ananas Comosus ◽  
Optimum Operating ◽  
Cellulose Content ◽  
Optimum Operating Condition ◽  
Operating Condition ◽  
Cellulase Enzyme

Pineapple leaf waste is one agricultural waste that has high cellulose content. Pineapple leaf waste's complex structure contains a bundle of packed fiber that makes it hard to remove lignin and hemicellulose structure, so challenging to produce reducing sugar. Dried pineapple leaf waste pretreated with a grinder to break its complex structure. Delignification process using 2% w/v NaOH solution at 87oC for 60 minutes has been carried out to remove lignin and hemicellulose structure so reducing sugar could be produced. Delignified pineapple leaf waste has been enzymatic hydrolyzed using cellulase enzyme (6 mL, 7 mL, and 8 mL) to produce reducing sugar. The sample was incubated in an incubator shaker at 155 rpm at 45, 55, and 60oC for 72 hours. Determination of reducing sugar yield had been carried out using the Dubois method and HPLC. The model indicated that the optimum operating condition of enzymatic hydrolysis is 7 mL of cellulase enzyme at 55oC to produce 96,673 mg/L reducing sugar. This result indicated that the enzymatic hydrolysis operating condition improved the reducing sugar yield from pineapple leaf waste. The optimum reducing sugar yield can produce biofuel by the saccharification process.

A Back Allocation Methodology to Estimate the Real-Time Flow and Assist Production Monitoring

2021 ◽  
Author(s):  
Gabriela Chaves ◽  
Danielle Monteiro ◽  
Virgilio José Martins Ferreira
Keyword(s):  
Real Time ◽  
Input Data ◽  
Oil Field ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Time Flow ◽  
Well Model ◽  
Operational Information ◽  
The Individual

Abstract Commingle production nodes are standard practice in the industry to combine multiple segments into one. This practice is adopted at the subsurface or surface to reduce costs, elements (e.g. pipes), and space. However, it leads to one problem: determine the rates of the single elements. This problem is recurrently solved in the platform scenario using the back allocation approach, where the total platform flowrate is used to obtain the individual wells’ flowrates. The wells’ flowrates are crucial to monitor, manage and make operational decisions in order to optimize field production. This work combined outflow (well and flowline) simulation, reservoir inflow, algorithms, and an optimization problem to calculate the wells’ flowrates and give a status about the current well state. Wells stated as unsuited indicates either the input data, the well model, or the well is behaving not as expected. The well status is valuable operational information that can be interpreted, for instance, to indicate the need for a new well testing, or as reliability rate for simulations run. The well flowrates are calculated considering three scenarios the probable, minimum and maximum. Real-time data is used as input data and production well test is used to tune and update well model and parameters routinely. The methodology was applied using a representative offshore oil field with 14 producing wells for two-years production time. The back allocation methodology showed robustness in all cases, labeling the wells properly, calculating the flowrates, and honoring the platform flowrate.

RANCANG BANGUN TRACKING ARAH TEMBAKAN MENGGUNAKAN SENSOR POSISI BERBASIS PID

2021 ◽  
Vol 7 (1) ◽  
pp. 43-48
Author(s):  
Agung Raharjo ◽  
Eko Kuncoro ◽  
Imam Azhar
Keyword(s):  
Real Time ◽  
Data Communication ◽  
Raspberry Pi ◽  
Long Distance ◽  
Visualization System ◽  
Control Command ◽  
Combat Unit ◽  
Army Personnel ◽  
Automation Technology ◽  
Research Show

Seiring dengan perkembangan teknologi komunikasi dan otomasi, pelaksanaan tugas militer dapat dibantu dengan mengembangkan alutsista militer. Salah satunya pengembangan robot tempur yang akan digunakan sebagai alat untuk membantu tugas operasi jarak jauh pada satuan tempur TNI AD. Pada robot tempur tersebut akan ditanamkan sistem komunikasi data berupa perintah kendali laju robot, perintah kendali senjata serang, dan sistem visualisasi yang dapat digunakan untuk mendukung pergerakan robot hingga mencapai sasaran yang ditentukan, serta sebagai sistem penginderaan jarak jauh robot tempur untuk memonitor area musuh yang akan ditinjau. Operator menggunakan sebuah joystick untuk mengendalikan robot tempur dan tablet Android untuk memantau dan mendeteksi arah sasaran. Penelitian ini membahas tentang perancangan pendeteksian sasaran tembak yang dapat dikendalikan dari jarak jauh. Metode yang digunakan adalah metode eksperimen berbasis PID. Penelitian ini berfokus pada pendeteksian sasaran tembak yang nantinya akan terhubung dengan Raspberry Pi 3, sehingga senjata dapat mendeteksi adanya sasaran tembak yang ada di dalam jangkauan sensor posisi. Hasil dari penelitian menunjukkan bahwa robot dapat dikendalikan dengan mudah menggunakan joystick dan secara real-time terlihat pada layar Android yang terpasang pada kontrol joystick tersebut. Selain itu, sistem juga dapat membedakan antara sasaran tembak dan objek yang bukan sasaran tembak. Penelitian ini diharapkan dapat mendukung tugas operasi personel TNI dalam menjalankan misinya dengan memanfaatkan robot tempur. Along with the development of communication and automation technology, the implementation of military duties can be assisted by developing military defense equipment. One of them is the development of a combat robot that will be used as a tool to assist the task of long-distance operations on the Army combat unit. In the combat robot, a data communication system will be implanted in the form of a robot rate control command, an attack weapon control command, and a visualization system that is used to support the robot's movement to reach the target specified as a combat robot's remote sensing system for monitoring enemy areas to be reviewed. The operator has used a joystick to control the combat robot and to detect the direction of the target can be monitored with an android tablet. This research discusses the design of the detection of target fire that can be controlled remotely. The method used is experimental based on PID. This research focused on detecting firing targets that will be connected with Raspberry Pi 3 so that the weapon can detect the presence of firing targets within the position sensor. The results of the research show that the robot can be easily controlled using a Joystick and in real-time visible on the Android screen mounted on the Joystick control, the system can distinguish between target shooting and non-target objects. This research is expected to support the operational duties of army personnel in carrying out their missions by utilizing combat robots.

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.

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