bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancing Energy Performance Monitoring of Large Compression Units Using a Thermodynamic Digital Twin
Authors: Alzaabi Y. S. , Sajjad S. S.
Published: October 2023

The compression units installed on the sales gas network encounter a diverse range of operating modes due to the fluctuating supply and demand conditions and the corresponding dynamics of the network. Determining the actual performance in such applications creates a significant challenge due to the variability of specific energy consumption. This paper introduces a new and reliable monitoring system that allows for real-time assessment of energy performance in dynamic compression. The system also identifies potential applications for energy conservation.

The methodology involved a comprehensive examination of the design and original equipment manufacturer (OEM) data associated to the compression units. This was subsequently followed by an in-depth review of the operating envelope. Afterwards, a comprehensive thermodynamic model was developed for compression units that incorporates all operational modes. The model was then confirmed using real operational data by integrating the OEM's actual performance curves into the thermodynamic digital twin. In order to facilitate the monitoring of compressor performance when the thermodynamic digital twin is not available, an additional mathematical model has been developed alongside the existing thermodynamic model. This supplementary model allows operators to conduct off-line monitoring of the compressors.

Conducting a comprehensive performance analysis of centrifugal compressors is imperative in order to accurately assess their operational status and efficiency. A decline in performance can serve as an indicator of internal wear or fouling, which, if left unaddressed, may lead to diminished throughput, increased energy consumption, or unexpected interruptions in operation. Hence, the performance metric encompasses not only energy consumption and operational expenses, but also encompasses critical factors such as reliability.

The development of an integrated thermodynamic digital twin for large sales gas compression units, which possess a total throughput capacity exceeding 500 MMSCFD, has facilitated and exhibited efficient energy performance monitoring, even in the presence of varying operating scenarios. The tool enabled the immediate comparison between the actual performance, specifically the energy consumption, and the anticipated performance based on the model. Additionally, it facilitated immediate tracking of polytropic efficiency trends and provided a real-time visualization of potential opportunities for energy savings.

The digital twin has demonstrated its efficacy as a cost-effective and dependable tool for real-time prediction of compressor performance across different operational modes. The information obtained from the compression digital twin can be integrated with process simulation models to enhance the optimization of the overall process. The model has the potential to enhance supervisory capabilities, diagnostics, control capabilities, and even aid in the prediction of failures in advance.
Application of a Digital Twin for Asset-Wide Production Planning and Optimization – A Case Study
Authors: Atibodhi N. , Toprasert P. , Thienthanukit W. , Supha-Kitti D. , Pongsripian W. , Wang F. , Luengo E. , Nazir F. , Mijares G.
Published: October 2023

This paper presents the results and insights gained from implementing a Digital Twin within the context of a Production Planning and Optimization (PPO) solution. The paper shares the framework and principles of Production Planning and Optimization and the way they drive the requirements and use of the Digital Twin to allow for the effective solution of the planning and optimization problem. In particular, it highlights the requirement of a model of record and an "evergreen" Digital Twin that should include the automated processes to assess the quality of the data consumed, to update the model when changes to the design or operation occur, and to calibrate the model using the latest data available.

A Case Study of an implementation of a Short-Term Production Planning and Optimization (STPPO) solution for over a thousand wells and hundred platforms in three offshore gas fields in Thailand is presented. The solution helps the end user to carry the short-term production planning and optimization for the fields within the presented context, allowing for the definition of daily production and operational targets for all the wells in the asset to meet a desired production target while observing operating and product quality constraints.

The Case Study is implemented within the PPO framework introduced in the paper thus allowing for the future functionality expansion, such as the integration to a Long-Term Production Planning and Optimization (LTPPO), through the incorporation of constraints focused on longer term value drivers of the asset, such as recovery and other reservoir management indicators. Because of this, the solution is well posed to help closing the gap between the Reservoir and Production/Operations personnel and to support multidisciplinary collaboration.

The Case Study not only presents the technical details of the solution, but more importantly it highlights the challenges encountered in its implementation and adoption by the user. Specially, it underlines the importance to plan and implement continuous enhancement processes to align the solution and governance system, work processes, and operating culture to maximize user adoption and return on investment.
Predictive Maintenance of Heat Exchangers Using Digital Twin Models Systematic Literature Review
Authors: Huzaifa A J
Published: October 2023

Predictive maintenance plays a crucial role in enhancing heat exchanger efficiency by minimizing fouling-related performance degradation. This systematic literature review examines digital twin models for accurately predicting fouling and optimizing maintenance schedules in heat exchangers. The review covers recent research exploring the application of various digital twin models in predicting fouling in different industries. It also covers how much efficiency can be achieved by implementing prediction-based maintenance. The analysis of existing literature shows that the digital twin models are up to 99% accurate in predicting fouling, remaining useful life (RUL), and other performance parameters. Synthesis of the literature review also reveals that the implementation of predictive maintenance enhances operational efficiency, reducing the cost of maintenance and contributing to a sustainable and resource-optimized future for industries. The research aims to provide practical recommendations for businesses to implement digital twin models effectively in order to enhance heat exchanger efficiency and reduce maintenance costs. Moreover, this review identifies the need for further research to develop a comprehensive digital twin model tailored for predictive maintenance, calibrated using real-world data and scenarios.
Well Hookup Acceleration by X-Mas Tree Prediction
Authors: S. M. , T. K. , A. A.
Published: October 2023

Well hook up is one of the most important steps to put new wells into production. Usually, well hook up starts in an early phase of the project through the engineering phase. This phase will define the well hook up requirements depending on the nature of the well. The well could be an oil producer, a gas producer or an injector well. Based on the well type, different considerations will be adopted in view of the Well design, the drilling rig requirement and the predefined well setup. Once completed, the wells need to be swiftly connected to the production system through a set of instruments and piping hook up spools.

However, there is always an uncertainty about the final hook up spool due to its three-dimensional nature and the requirement of having a physical check (site survey) to initiate the spool prefabrication. This step could only take place after the X- Mas tree installation which will add extra days for the prefabrication and the installation of the final spool and will further delays the start-up.

In addition to that, the fact that we were recently in a worldwide Covid-19 situation with a heavy sanitary protocol with restriction on site mobilization and site POB (personnel on board) reduction, made the situation even worse and contributed to generating more delays on our hookup activities.
Robotics Application in Hazardous Operation and Construction
Authors: Mehta J. , Alshaali M.
Published: October 2023

Robotics have the potential to provide significant value to the construction, engineering design, operation, and maintenance activities. It provides a solution to capture required data from complex/ hazardous working environments by means of robotics tools and reduces the safety concerns for personnel by eliminating entry in a hazardous environment.

The main objective of this paper is to provide a solution that eliminates the risks of working in confined spaces and in preventive maintenance using robotics technology in dangerous environments. Robotics solutions can minimize risk and provide a method of acquiring site data, performing inspection and maintenance in an autonomous manner.

Data acquired can combine the use of robotics with AI (Artificial intelligence) to allow the machine to perform the tasks required accurately without human intervention. Many of the challenges faced at the project site may be resolved when applying this technology to the work environment. Application in plants containing hazardous gases and offshore unmanned environment will benefit from these technologies drastically. It leads to increased reliability of the project while reducing the risk of harsh operating conditions.
Drilling Digital Twin Predicts Drilling Dysfunctions and Performance in Real Time
Authors: Gandikota R. A. , Chennoufi N. , Saxena S. , Schellenberg B. , Groover A.
Published: October 2023

In the new digital age, improving drilling economics with tools like simulation and predictive analytics are key to enabling digital transformation. A novel real time digital twin has been developed to predict drilling dysfunctions and improve operational efficiencies. Real time surface (EDR) data with full physics time domain models are used to predict drilling dynamics and drilling dysfunctions in the bottom hole assembly at any depth. This provides a rare insight for drilling engineers to improve drilling performance and take predictive or corrective measures for reliability and operational efficiencies.

In the study presented here, the digital twin uses real time surface along with the details of bottom hole assemblies and drillstring to predict downhole drilling dynamics responses. Detailed information of the formation, drill string, bottom hole assembly and drill bit mechanics are utilized. A fast-running time domain models based on mixed multi-body mechanics and finite element methods form the basis of the digital twin. The workflow is built to automatically recognize drilling rig states (rotary or slide drilling) and connection makeup to start and stop the predictive model. The real time integration has been tested over several wells for stability and performance metrics. With the integration of real time data, the digital twin systematically predicts ahead the true WOB, bit RPM and downhole MSE. The integration of surface data to real time models makes it a true digital twin.
Next Gen of Field Operation Era for Artificial Lift Real-Time Monitoring: A Method to Significantly Optimize Oil Production of Mature Field
Authors: Hidayat A. , Isnanto S. , Lazuardi H. , Kurniawan C. , Kusuma H. , Ramadhan G. B. , Santoso H. B. , Hesti K. , Handarianto H.
Published: October 2023

Block X was one of the oil blocks in South Sumatra with more than 100 wells. It was previously monitored manually by the operator. Considering the cost and feasibility, IoT surveillance and optimization were implemented. This paper discusses the benefits of IoT optimization systems implemented in mature field.

The IoT optimization system includes wells such as ESP wells and SRP wells. Each well was already equipped with its control system. This project integrates the existing controllers with simple equipment that read data from the controller and transmits it to users. To the current system, automation culture was introduced. Dense data that has been collected from the controllers remotely were used to implement quick optimization analysis to give a responsive solution unique to each well. The benefits of these methods were closely observed and analyzed to determine whether the project has a long-term benefit going forward.

Three types of improvement were recorded during the project. Enhanced production due to well optimization, uptime maximization due to quick response, and operation efficiency by implementing automation system to the wells. With the optimization system, wells could be quickly identified which can be optimized. Operator could hasten the process by using a workflow that captures important parameters to be observed for optimizing the wells. Well's uptime was maximized by implementing a well down alert system. Alert system that was implemented included well rates and well location for operators to decide which well needed to be prioritized. This system managed to reduce loss oil potential (LPO) by 25% compared to the previous state where IoT optimization system was not applied. The implementation of automation for each well erased the need of manual visits by operators. Trips by operators were lessened by a significant amount and now could use their time for other critical wells.

The project managed to save over $500,000 and gain production equal to the value of $680,000 per month with the addition of possible gain up to $850,000. Cost-benefit of the project showed that the moderate cost invested at the beginning quickly was overshadowed by the benefits given in the following months.

This paper serves as a case study for future reference on the benefits of implementing IoT SCADA to one's field by integrating existing assets. Relatively low investment and the simple method of implementation would serve as a guide for others to embrace IoT surveillance and optimization system.
Successful Deployment of Unmanned Survey Vessel for Offshore Project - Opens New World of Opportunities
Authors: Srinivasan Ashish , Athmaram Jayaprakash , Shamsi Marwan Al , Seiari Abdul Hakeem Al , Bouremel Djaafar
Published: October 2023

ADNOC is in the process of connecting Abu Dhabi's offshore sites to onshore electricity grid by the year 2025, through subsea transmission network that is expected to reduce costs and replace gas used for power generation. As part of the project tender, ADNOC was required to submit Geophysical Seabed Survey for two cable routes from Abu Dhabi mainland to target offshore sites (approx. 180km). ADNOC Offshore survey team were assigned with the task. Capitalizing on its technical industrial partners, ADNOC Offshore took the initiative to deploy several surveying technologies with one being deployed for the first time. An Unmanned Survey Vessel (USV) was deployed for one of the challenging nearshore segments of the route (for 24km) for the very first time in UAE waters for engineering design requirements. The unmanned hydrographic survey vessel was remotely controlled using telemetry solution including Domo Tactical Communications (DTC) radio and 4G communication system to overcome several onsite data acquisition challenges, which enabled project delivery for fraction of a cost while complying with high quality standards including operational flexibility for very shallow areas and absolutely no exposure of personnel. The company not only managed to deliver the entire geophysical data requirement on time, but also introduced a new technology that will open a new world of potential applications in the marine operations like surveillance, patrolling, geophysical surveys, light cargo shipping over short distance, etc. This will bring sustainable efficiency and effectiveness to marine operations and substantially save operational costs on large-scale implementation.
Using Multilinear Regression to Predict Key Engineering Quantities for Estimation in EPC Projects
Authors: Banotra R. , Peace S. R. J.
Published: October 2023

Objective

The Engineering, Procurement and Construction (EPC) industry has been slow to adopt data-driven Artificial Intelligence (AI) and Machine Learning (ML) systems. Decentralized data storages make data engineering a challenging task, highlighting a recognizable shortage of harnessing data from these data storages, and using ML to optimize estimations for large EPC projects.

Empowering proposal teams by using ML-based tools on the engineering disciplines data from previously executed projects can help them make better cost estimates and more informed decisions during project execution.

Methods, Procedures, Process

The McDermott AI team and domain Subject Matter Experts (SMEs) worked together to improve the process of using initial bills of quantities (BOQ) / Material take-off (MTO) for cost estimation during early stages of the project bidding. We combined the knowledge of EPC engineering experience and data into a real-life application - a ML-based multilinear regression application to predict MTO quantities for different engineering disciplines using MTO data from previously executed projects within the company. The database was developed by compiling MTO data from past projects and applying feature engineering on it. An example material quantity prediction is in Figure 1.

Results and Conclusions

As organizations look to modernize and optimize processes, ML is an increasingly powerful tool to drive automation. Unlike basic, rule- based automation—which is typically used for standardized, predictable processes—ML can handle more complex processes and learn over time, leading to greater improvements in accuracy and efficiency. The developed ML-based software can help proposal teams to improve initial cost estimates for engineering disciplines key quantities. In addition to this, in the paper we also share our experience and lessons learnt on how to prepare database from decentralized data banks, and how we can pre-process this data for our machine learning model.

Novel/ Technical contributions

The main aim of the developed ML solution is to harness the power of EPC project data and experience to improve work hour or cost estimation for engineering disciplines. The model has been developed using data from different types of EPC projects executed all around the world. This also presents a case on why and how companies can best utilize the data which is usually stored in decentralized data storage. The solution can assist proposal teams to make better estimates for scope of work based on the type of project. This product could be potentially applied to any EPC company working on oil & gas or petrochemical plants. It could also motivate other practitioners and researchers to replicate the experience to develop a similar tailor-made ML solution for different industries.
Enhanced Explosion Risk Management Through Ex-RBI and Data Analytics: Implementation Strategies and Case Study
Authors: Harris Raja Fernaliz Raja , Zaharin Muhammad Naiem Naqiuddin , Yahaya Ahmad Fairuz
Published: October 2023

A Risk-Based Inspection (RBI) framework for electrical equipment for hazardous areas (EEHA) by using Analytical Hierarchy Process (AHP) tool was presented in this paper. A case study at a facility with 789 electrical equipment operating in explosive atmospheres was conducted by analyzing the EEHA's risk-based inspection (Ex-RBI) results to determine the equipment's explosion risk. The results indicate 6% of the equipment has a high explosion risk. On the other end, 66% of the equipment falls into the low-risk category. Our analysis found that implementing Ex-RBI and data analytics strategies can significantly enhance explosion risk management in industrial settings. Through this study, we demonstrated that Ex-RBI can effectively identify and prioritize high-risk equipment and areas, allowing for targeted risk management efforts. Based on the explosion risk of each of equipment, a strategy can be developed to decide on the prioritization for maintenance activity, the interval of periodic inspection, and the grade of inspection for the next inspection cycle. The case study demonstrates enhanced explosion risk management leading to operational excellence by leveraging Ex-RBI and data analytics. Facility owners can identify and mitigate potential risks before they become critical. Over a period, this leads to reduced explosion risk, a more cost-effective maintenance programme and improved overall safety.
Field Development Opportunities Unveiled in Low Resistivity Reservoirs, Sub-Andean Oil & Gas Reservoirs
Authors: Bustos U. D. , Quiroga D. , Tapia O. , Mosquera C.
Published: October 2023

Driven by strong initiatives of leveraging hydrocarbon production in Bolivia and reducing imports, YPFB-Andina started assessing development opportunities in Devonian, Cretaceous and Tertiary rocks. From a textural point of view, these are fine grained sandstones with variable contents of quartz, feldspars, low clay content and porosities in the 15% range. Conventional induction logs response exhibits low resistivity (below 10 ohm.m), meanwhile advanced triaxial induction confirms that electrical properties are mostly isotropic. Consequently, despite hydrocarbons being shown while drilling, conventional petrophysics suggest these reservoirs are water bearing. With the aim of ensuring the real potential hydrocarbon occurrence, we incorporate hydrogen-independent fast neutron cross section (FNXS) and total organic carbon (TOC) from a slim spectroscopy device and transverse relaxation times distribution (T2) from a pad-type nuclear magnetic resonance tool.
Design and Testing of Al Enabled Non-Radioactive Multiphase Fraction Meter
Authors: Akram Karimi Muhammad , Arsalan Muhammad , Shamim Atif
Published: October 2023

Multiphase flowmeters (MPFM) are commonly used in O&G industry to monitor & optimize production in real time. However, existing multiphase flow meters are either intrusive, radioactive or don't cover full range without requiring frequent calibration. Gases have much different density than liquids and the mixture density is linearly related with the fluid fractions over the full range but the devices to measure density either possess moving parts or rely on radioactive sources (e.g., gamma rays), which are hazardous. On the other hand, some non-density based MPFM relying on dielectric properties of multiphase mixture can be implemented without moving parts, but the dielectric properties have highly non-linear and non-monotonic response with respect to salinity of the produced water, making it extremely complicated to implement. That is why, existing dielectric based MPFM also use a radioactive source specially to measure gas volume fraction (GVF). This paper presents a novel non-radioactive microwave DMOR technology which solves the complex non-linear problem with the use of a digital twin model and custom designed AI algorithm. This unique approach provides a non-intrusive and non-radioactive solution to reliably measure the multiphase fractions without being dependent on fluid mixing conditions.
From Conventional Dips to Geological Features Mask Generation for Advanced Borehole Analysis
Authors: Petrov A. , Belayouni N. , Belouahchia M. , Xin L. , Fan Y. , Leseur N.
Published: October 2023

The Al-based identification of borehole images by means of supervised learning techniques has recently made significant progresses to automate some of the routine interpretations carried out by borehole geologists. While deep-learning approaches have the power to significantly trim down repetitive gee-tasks, they also require a large number of annotations to accurately assist the practitioner in its day-to-day work. When it comes to borehole image interpretation, typical annotations come into the shape of an idealized sinusoid lines delineating sedimentary or structural objects such as the boundary between two geological beds. In view of extracting petrophysical and geomechanical properties at the bed level for subsequent net pay analysis, industry-standard dip picking interpretations can be used to guide the time-consuming contouring of each bed by means of customized segmentation approach.

To start with, patches of the entire borehole image are extracted around the areas where an interpreted sinusoid is available. Then, for each individual patches, a map of the distance between each pixel and the latter sinusoid is calculated. Acting as weighting spatial property emphasizing the most predominant foreground feature, such distance-based map is subsequently added as an additional channel to each image patches. Finally, the latter image patches are used as inputs to train an instance segmentation algorithm generating binary masks for each geological beds and comparing them to a set of subject matter expert interpretations.

Overall, the new method succeeded in automatically segmenting geological beds from commonly available industry-standard borehole interpretations with more than 80% accuracy on average-to-good image quality intervals. While this type of technology significantly alleviates the need for time and cost-intensive manual labeling, it is also seen as a promising approach to implement advanced semantic search of geodata bases as well as a more robust and systematic net pay analysis of thinly laminated low-resistivity reservoirs.

While Al-ready data vs. Industry-legacy data have not been designed to be mutually convertible, recent advances in the field of computer vision provide a solution to preserve the value of past information for nowadays Al-training purposes. Though the current method augment modern-day BHI SMEs with a digital companion for repetitive tasks, human-in-the-loop is still required to handle around 20% of the work depending on the quality of the well. The current techniques was developed in a limited time period and could be improved through grid search optimization, better filtering of input images and dip interpretations. This work aligns with current trends in the field of Al, trying to alleviate the traditional need for extensive human labelling to feed supervised learning models. Other future areas of research to look at self-supervised and few-shots learning.
Experimental Investigation of Hydrocarbon and Non-Hydrocarbon Gas Injection in a Tight Danish North Sea Oil Reservoir
Authors: Mokhtari R. , Talaei A. , Feilberg K.
Published: October 2023

Lower Cretaceous oil reservoirs in the Danish part of the North Sea, are generally deep, with high porosity and very low permeability rock, which makes the applicability of any EOR method and any reservoir development plan challenging. One potentially feasible enhanced oil recovery (EOR) method is the gas injection, where the produced gas, flue gas, and CO2 have sufficient injectivity to be the candidates. Therefore, this study aims to assess the applicability of gas injection as an EOR method for the challenging Lower Cretaceous oil reservoirs in the Danish North Sea. To exclude the effect of rock quality on recovery results, a single core plug from the Lower Cretaceous Tuxen formation without any open longitudinal fractures was selected, cleaned, and re-used for all experiments. The clean and dry core was saturated with formation water, and after that, the irreducible water saturation was achieved by displacing the water with dead crude oil. The dead oil was then displaced by live oil after four weeks of aging. The gas injection experiments afterward were conducted at two different pressures, 250 and 350 bar (current and initial reservoir pressures, respectively), and the reservoir temperature of 85 °C. During the experiments, effluent fluid density, differential pressure response across the core, and effluent gas flow rate are recorded in addition to the recovery data. This makes it possible to evaluate the two/three-phase flow characteristics accurately. The initial scenarios investigated are hydrocarbon gas injection, in this case, synthetic natural gas, at two different pressures. The results show that the recovery factor for the hydrocarbon gas injection is significantly higher at 350 bar (at near miscible condition) compared to 250 bar. Conversely, Since CO2 is at the supercritical condition at both 250 and 350 bar at 85 °C, and is fully miscible with oil at both pressures, no significant difference is expected at different injection pressures for CO2. Unlike, flue gas is immiscible at both pressures, showed a significantly lower recovery factor compared to natural gas and CO2. However, comparing the efficiency of hydrocarbon gases and CO2 is of great interest for the choice of gas for injection. The produced hydrocarbon gas might be most readily available, however, CO2 injection includes the potential for storage of the injection gas.
API Pipeline Safety Management Systems: Assessments Updates and Contractor Safety Programs
Authors: Frazier C. M. , Knape L. A.
Published: October 2023

The API Pipeline Safety Management System (Pipeline SMS) Assessment Program continues to provide a not-for-profit industry-accredited option for pipeline operators to assess their safety management system. In addition to assessments and gauging Pipeline SMS maturity, the Pipeline SMS Industry Team has also worked to produce guidance to help operators and contractors/service providers understand and align their safety programs. Here, API will review key assessment findings to date as well as highlight the tools we have created for contractors/service providers to implement Pipeline SMS.

The API Pipeline SMS Assessment Program has conducted assessments at 17 pipeline operators in North America, representing small and large operators in both the liquid and gas product businesses. In March 2023, API updated its benchmarking database and analyzed it to verify if previous trends continued and if we have seen improvements in lower scoring areas. Trends and themes will be discussed, as well as API's work to assist industry in these areas.

Positively, pipeline operators around North America have acknowledged the need to leadership to embody safety values and make those values evident to their employees and contractors. In addition, and in alignment with leadership presence, safety culture of front-line staff continues to be one of the highest scoring areas. Another area of positive feedback from benchmarking is with emergency preparedness and response, with most sites receiving very high marks for this management system element.

However, some areas require more focus. In North America, operators are required to make external stakeholders (e.g., the government, the public, those with land that abuts the pipeline right-of-way, police, emergency services, etc.) aware of their operations and safety efforts, and provide them a mechanism to give operators feedback; this is an area where API has seen lower scoring. However, in the past year, API has seen improvements to the maturity performance in this area.

One theme is that many operators voice concern over management of contractor/service provider safety programs. This led API to create a Pipeline SMS Contractor Guide, as well as contractor implementation tools to help implement and gauge maturity of safety programs. Both the Guide and the Tools are available free of charge on www.pipelinesms.org and will be demonstrated here.

Pipeline SMS and API RP 1173 support the API Energy Excellence® Program, a program that helps operators implement overarching management systems through thirteen (13) elements in support of operational excellence across all segments of operations. There are few, if any, published guidance documents on a management system framework that can be applied to all segments. In addition, the contractor materials add to the suite of materials aiding industry in operational excellence.
Phase Behaviour and Physical Properties of Dimethyl Ether (DME)/CO2/N2/Water/Heavy Oil Systems Under Reservoir Conditions
Authors: Li Yunlong , Huang Desheng , Dong Xiaomeng , Yang Daoyong
Published: October 2023

The application of a mixture of dimethyl ether (DME) and flue gas is a promising method to recover heavy oil as DME is first-contact miscible with hydrocarbons and partially miscible with water, CO2 can accelerate mass transfer, and N2 can boost the energy in a depleted heavy oil reservoir; however, phase behaviour and physical properties of DME/CO2/N2/water/heavy oil systems are still not well quantified. In this study, theoretical and experimental techniques are developed to determine phase behaviour and physical properties of the aforementioned systems at pressures ranging from 2 MPa to 20 MPa and temperatures spanning from 352.15 K to 433.15 K. In addition to collecting experimental data from the public domain, eight constant composition expansion (CCE) tests are carried out. A thermodynamic model that incorporated the Peng-Robinson equation of state (PR EOS), a modified alpha function, the Péneloux volume-translation strategy, and the Huron-Vidal (HV) mixing rule is used to reproduce the measured phase equilibria data. The tuned binary interaction parameters (BIPs) are utilized in conjunction with the thermodynamic model to accurately predict saturation pressure (Psat) and swelling factor (SFs) with a root-mean-squared relative error (RMSRE) of 3.32% and 0.57%, respectively. Furthermore, the recently proposed model demonstrates its high accuracy in forecasting the oleic/vapor (LV) two-phase boundaries for N2/heavy oil systems and DME/CO2/heavy oil systems with an RMSRE of 1.93% and 2.77%, respectively. Similarly, the accuracies of the predicted aqueous/oleic/vapor (ALV) three-phase boundaries for N2/water/heavy oil systems and DME/CO2/water/heavy oil systems are 2.85% and 3.47%, respectively. Besides, water is found to increase the phase boundaries for DME/CO2/heavy oil systems but decrease those of N2/heavy oil systems and DME/CO2/N2/heavy oil systems. Additionally, as the concentration of N2 and CO2 in the feed mixture is increased, its Psat is increased. In this work, new PVT experiments are conducted to evaluate the impact of adding DME/CO2/N2 into the heavy oil bulk phase in the absence and presence of water. The developed model accurately characterizes the phase boundaries and physical characteristics of the reservoir fluids containing polar components, which are essential for design, evaluation, and optimization of hybrid steam-solvent injection processes in heavy oil reservoirs.
HSURF: A New Modular Platform for Underwater Remote Semi-Autonomous Facilities Inspection
Authors: Iacoponi S. , Alhosani H. , Mankovskii N. , Infanti A. , Zhilin I. , Renda F. , Stefanini C. , De Masi G.
Published: October 2023

In this paper we present the H-SURF modular system, consisting of three different platforms (floater, sinker and fish), that can be used for underwater wireless telecontrolled inspection. Differently from the most common commercial approaches where tethered big ROVs are used for subsea inspection, here many small untethered semiautonomous robots are used, oriented to a robotic swarm concept. The full system allows teleoperation from a remote base station and inspection of complex subsea structures consisting of several tubes and valves, taking benefit of the collaboration among different platforms and many small and flexible robots. We show the testing results of telecontroled navigation in a very complex trajectory and a semiautonomous detailed inspection of a submersed vertical structure.
Light Weight Tomographic Monitoring of Pipe Wall Thickness
Authors: Instanes Geir , Pedersen Audun O. , Simonetti Francesco , Nagy Peter B.
Published: October 2023

Tomographic methods are used with ultrasonic guided wave wall thickness monitors to provide two-dimensional maps of the wall thickness throughout a monitored area. Tomographic monitoring systems are typically configured with 16 to 32 non-intrusive ultrasound transducers positioned in predetermined patterns for optimal coverage and resolution. Other monitoring systems have much fewer transducers, positioned according to the pipe geometry and wall area of main concern. Although these systems are not optimized for wall thickness mapping, the same or similar tomographic methods can improve analysis and interpretation of the datasets they produce. Algorithms are sought for implementation in responsive, interactive software for browsing and analysis of recorded wall thickness monitoring data. Simple tomographic algorithms are also desirable for use in embedded software. A "light weight" tomographic algorithm is outlined, and a prototype implementation is tested against a proven full-scale tomography software package. The two approaches produce similar results on small datasets corresponding to wall thickness monitoring systems with few transducers installed. For the larger datasets generated for high resolution wall thickness mapping, the reference software is superior in terms of both computational load and accuracy.
Successful Velocity String Deployment Pilot to Improve Productivity and Sustainable Gas Recovery for Three Sub-Optimal Completion Wells in Oman Block-61
Authors: Al Darai A. , Al Fadhli K. , Al Harrasi S. , Najwani M. A. , Raji A. , Qamar O. , Villarroel P. , Daoud S. , van der Ven B.
Published: October 2023

Block 61 is a gas field, located in Oman, characterized by tight reservoirs. Majority of the vertical wells in the field are completed with 4½″ to 5½″ production tubing. As wells continued to produce over time, a decline in the production was observed due to liquid loading. A Sustainable option to enhance production recovery was introduced. This involved reducing the current production tubing internal diameter (ID) and area. To accomplish this without compromising the reservoir, a velocity string (VS), using a snubbing unit, was installed for three wells in effort to determine if it's fit for purpose for full field development.

(VS) wells were chosen based on specific selection criteria, mainly focusing on wells with reservoir pressure around 4,500 psi and different performance levels, to evaluate VS completion design and capabilities under various well conditions.

Three pilot candidate wells were completed with smaller sized velocity string completion tubing in Block 61. The installation was executed through a Snubbing unit with wellhead pressure control configuration in snubbing mode, resulting in the deployment of the VS under pressure. The benefits of this well intervention method is that it eliminates the potential for hydrate formation and reservoir damage since no kill fluid is pumped in the wellbore.

The VS completion design consists of jointed chrome pipes, completion components (Sliding Sleeve Door (SSD) & Wireline Entry Guide (WEG)) and a hang-off packer.

From an operational perspective, the wells were delivered safely with minimal non-productive time (NPT) and 31% ahead of schedule. This resulted from the continuous and proactive implementation of lessons learned, which were captured during the VS installation operations.

This paper will cover the valuable lesson learned to help drive efficiency and optimization of future planned campaigns.

Moreover, post VS installation, the 3 pilot candidate wells were brought back to production. The production rates from the candidate wells showed initial positive results flowing through the VS completion as predicted during the project design and planning.

The application of the snubbing unit for bp Oman was the first successful VS installation in Block 61. This effective deployment presents an opportunity to extend the production life for over two hundred wells in Block 61 with high efficiency when intervening on these wells. The objective of this paper is to summarize the journey of installation of velocity strings in Block 61, aiming to cover aspects such as planning, design, wellbore preparation, operational execution and well performance results post installationBody text 1 paragraph.
Systematic Talent Management & Succession Planning
Authors: Taechasapasith T. , Silakorn N.
Published: October 2023

This paper demonstrates how systematic Succession Planning is important to PTTEP business especially when we operate over 50 petroleum exploration, development, and production projects in more than 10 countries across several regions with the primary focus on Southeast Asia and the Middle East as well as other petroleum-prolific areas displaying investment opportunities, both E&P and beyond E&P businesses. It ensures that all critical positions are occupied continuously and gains more engagement from the PTTEP talent pool.

In 2020, Succession Planning became one of the KPIs among Top Management resulting in "1st time solid Succession Planning". Career Review Committee comprises CEO and Top executives responsible for identifying, developing, and retaining talent and succession planning so we can sustain our strategy of "strengthen leadership to a sustainable organization." We partnered with a global consulting company for a talent assessment tool based on talent models and benchmarks using a nine-box grid matrix of potential together with performance and other consideration factors for talent identification. Once successors are identified, the Company designs an Individual Development Plan (IDP) which consists of a career rotation plan and development framework.

With strong support from all management, in 2021 we achieved a set of solid succession planning to support business growth with a successor ratio of more than three successors in all executive posts. Since then, PTTEP management movement and appointment have been considered systematically and even more efficiently through a practical end-to-end talent management process, starting from talent assessment to identify talent and successor, and development to ensure readiness. We completed 100% of the Individual Development Plan (IDP) focusing on both career plans and competency gap closing for talents. By developing various development programs including accelerated programs partnering with world-class institutions and leading consulting companies, leadership training courses, mentoring programs, executive talks, and networking programs both online and offline, we got a high satisfaction score of over 80%. Impactful succession planning also saves costs from internal development and placement without high external executive hiring costs. This upcoming year, the focus is how to prepare workforces to expand to our new territories in the Beyond E&P. With the new business requirement, therefore, we plan to encourage and provide talents with more career advancement opportunities to rotate across their discipline to achieve new career goals and more challenging job opportunities to expand the successor pool in the future.

This paper shows that systematic Succession Planning benefits the company as it keeps our workforce and talent pipeline stable. Its benefits, however, are not only for PTTEP itself but could be for the PTT Group as well, as it provides a valuable resource pool among them.
Prospect Focused Imaging Through Advance Seismic Driven High-Resolution Fluid Modeling Approach
Authors: Mukherjee Jagannath , Das Debjyoti , Chakraborty Dibakar
Published: October 2023

Petroleum Systems Modeling is a well-known workflow to evaluate the basin potential. However, in the prospect maturation stage, we mainly focus on reservoir and trap characterization. The lack of an established workflow to quantify the risks associated with seal integrity and preferred migration, is one of the main reasons for dry wells.

This establishes an innovative workflow and explores the value of coupling the regional scale insights into a prospect specific study in a field with existing discovery for exploration risk mitigation. An integrated fluid migration approach has been adopted to de-risk the prospect and predict the likely migration pathway in the petroleum system. This integrated workflow consists of detailed reservoir scale characterization using advanced seismic attributes, followed by static and dynamic migration simulation to envisage the local migration process within a high-resolution reservoir model to assess the sealing capacity of the cap rock.

A modified invasion percolation method has been used to evaluate the effect of buoyancy and capillary pressure driven hydrocarbon fluid migration in the high-resolution reservoir model and in turn, inspect the seal integrity to withhold the hydrocarbon column height. The fluid migration model was simulated with a multi-phase PVT model to estimate the hydrocarbon phase at the reservoir condition. A fluid mixing model was also built at the prospect scale to evaluate the fluid phase and composition understanding. This helped in estimating fluid distribution in the field scale in terms of phase and components of hydrocarbon. The seal integrity model involves detailed assessment of the PVT model along with wettability and interfacial tension of the rock properties for accurate prediction of the column height holding capacity. The model has been calibrated with the existing well data and production data in terms of hydrocarbon saturation and the tested fluid phase at the production well.

This novel approach can be positioned as an advanced quantification tool in prospect focused imaging where the risk parameters relating to migration and cap rock are also being evaluated without losing any information from the regional context. This new way of de-risking process can help to mitigate the potential risks associated with the petroleum systems elements to increase exploration success.