bluuebunny/crossref_metadata_2025 huggingface dataset:
Macroeconomic Impact of Sharia Business Unit of Indonesian Islamic Banking On Liquidity Asymmetric Approach
Authors: Hakim Muadz Abdul , Achsani Noer Azam , Saptono Imam Teguh
Published: October 2023

This study aims to determine the impact of macroeconomics on the liquidity of Indonesian Sharia Business Units (UUS). The liquidity in this study uses the Financing to Deposit Ratio (FDR). In contrast, the Macro Factors used are Inflation, Rupiah to Dollar Exchange Rate, BI Rate and Gross Domestic Product (GDP). The method used Nonlinear Autoregressive Distributed Lag (NARDL) method with data from January 2015 - June 2022. The results showed that in the long term, that affect UUS liquidity are Positive Rate, Negative Rate, Positive GDP, and Negative GDP, in the short term Inflation, Exchange Rate, Rate, and GDP are both positive and negative. Results show that UUS liquidity is vulnerable to changes in Indonesia's macroeconomic factors.
Surgical safety: effectiveness based on collective intelligence and implementation challenges (review)
Authors: Benyan A. S. , Korymasov E. A. , Chertukhina O. B. , Khranovsky D. G. , Medvedchikov-Ardiia M. A.
Published: October 2023

The authors used databases Scopus, PubMed, Web of Science, MedLine, RSCI for a systematic periodicals review on surgical safety issues published from 2000 to 2022. The literature review has shown that organization of interaction and communication, quality of completion of the checklist, assessment of the clinical effectiveness of the checklist, possibility of adapting the checklist to the conditions of a particular surgical department, increased compliance of healthcare professionals with the use of the surgical safety checklist, possibility of patient participation in completing the checklist appear to be the basic issues requiring a critical look and a prospective discussion. The introduction of individual components of quality control and medical care safety is known to be a rather long and staged process, during which systematic approaches, starting points and control points are repeatedly reviewed. The high level of specialists training and concentration, the need for clear communications within the surgical team, strict follow the preventive rules can serve as the initial guidelines requiring constant training control. The process principle of quality service management and the incorporation of new technologies for optimization filling and digitalization of the checklist will improve the efficiency and effectiveness of surgical safety.
Art as a path to public health: to the 320-year anniversary of St. Petersburg (on the example of the author’s project)
Authors: Saginbaev U. R.
Published: October 2023

Introduction. The article examines the important role of art and culture in ensuring public health. In particular, this method of informing the population seems to be the most digestible and memorable. In other words, a multidisciplinary approach can improve the efficiency and effectiveness of health care organization methods in terms of raising public awareness.

Target: raising public awareness of aspects of primary and secondary prevention (exemplified by ophthalmic pathology) through the collaboration of health organization with art and culture.

Methods. In the course of the work, methods of theoretical generalization, analysis of scientific literature, photographing, adapted image editing, compilation and distribution of sanitary pools, conducting a conversation with the population, and questionnaires were applied.

Results. Within the framework of the project «Jubilee Sanbulleti. 320 St. Petersburg «developed original sanitation, combining not only hygiene and prevention, but also aspects of culture and art. A high role in public health of approaches such as collaboration (collaboration) and interdisciplinary is noted.

Conclusion. The fundamental approaches of this project make it possible to integrate the foundations of primary and secondary prevention into almost all aspects of our activities, and such implementation is carried out evenly, without obsession. This property of the project correlates with the basic principles of modern health care – preventive and participative.
Buku Ajar Mata Kuliah Kesehatan Reproduksi dan nilai-nilai Islam Jilid 1
Authors:   Universitas Muhammadiyah Sidoarjo, Hanum Sri Mukhodim Faridah , Widowati Hesty
Published: October 2023

Berkat limpahan dan rahmat-Nya sehingga penulis mampu menyelesaikan buku Ajar “Kesehatan Reproduksi Dan Nilai-Nilai Islam“ yang tentunya diharapkan dapat memberikan kontribusi positif bagi pembaca khususnya mahasiswa.Sejauh ini Mata kuliah Kesehatan Reproduksi di berikan pada semua prodi kebidanan, di karenakan merupakan dasar dari mata kuliah yang terkait dengan terwujudnya kesehatan masyarakat yang optimal terutama kesehatan wanita, oleh karena itu sangat perlu kiranya ada panduan belajar berupa buku ajar kesehatan Reproduksi.
Artificial Intelligence and Data Analysis Approach to Deliver 5800 BOPD from Cyclic Steam Stimulation Job in Krakatau Field
Authors: Nainggolan Selvyn Anggreini Stephanie , Wilantara Dedi , Mutiaranti Reza , Pangastuti Resiayu Kinasih
Published: October 2023

Krakatau field was discovered in 1941 with an active steam flood operating in 1985. To maintain oil production, well intervention jobs become critical activities to perform at 6000 producers. Cyclic steam stimulation is one type of well intervention job that is a relatively low-cost and efficient method to improve well performance. The process involves injecting steam which allows oil heated by the steam to flow more easily.

Started 2015, cyclic stimulation activity levels raised up from 50 jobs/month to 350 jobs/month. The type of cyclic stimulation performed is called short cyclic stimulation, in which the objective is cleaning the wellbore from asphalt, resin, and paraffin deposit. The review candidate process is done by Petroleum Engineer manually, which potentially delivers inefficiency and inconsistent processes among the Engineers. Having this condition, the team search for opportunities to deliver shorter cyclic time of reviews and improved job success rate by developing an Artificial Intelligence Tool using an Artificial Neural Network (ANN) algorithm.

In 2022, cyclic jobs in Krakatau field successfully hit the highest execution at 525 jobs/month. The combination of an Artificial Intelligence Tool and visualization data tool in the form of Power BI for data analysis is very impactful to increase productivity and improve the job success ratio.

The team will elaborate on the subsurface parameters to develop Artificial Intelligence and analyze data processes to deliver cyclic gain performance in level 5,800 BOPD.
New Way to Converting Gas Wells into Oil Wells to Exceeding the Life of Mature Oil Field: Case Study at Handil Field, Mahakam Block, East Kalimantan, Indonesia
Authors: Umar Arsalan , Li Ulinnuha Iftitahul Lu’ayyi , Suhartanto Andrian , Maulana Muhammad Irfan , Wijaya Geraldie Lukman , Maz Nasuto Saidana , Setiawan Dedy , Risal Miftachul , Jamal Muhammad Nadrul , Pradana Theodorus Aditya , Suwito Edy , Hidayat Mas’un , Setiadi Rahman
Published: October 2023

Handil field is a giant oil field in Indonesia which started discovery since 1975. Currently, Handil Field has production around 12,000 bopd and 44 MMSCFD of gas. Through new wells data in the Handil Field from 2018 to 2022, there are around 55% of tubingless completion wells that have a main focus on producing gas reservoirs in the Handil Main Zone and Deep Zone. During drilling operation, sometimes it was found several oil reservoirs based on open hole logging result on well which will be completed by tubingless completion. To switch the completion from tubingless completion into oil well completion will make the well completion will be delayed, therefore the well will be completed with tubingless completion. Over time, where the gas reservoirs begin to deplete, there are still others oil reservoir layers in this well that wait to be produced. Due to low reservoir pressure and no gas lift facility in the tubingless well completion, thus these oil reservoirs cannot be produced. The previous solution that has been implemented is to do heavy workover, by cutting upper completion and replacing it with a new completion that includes a side pocket mandrel; or do a light workover by installing a Gas Lift Macaroni inside the existing tubing. Both solutions have disadvantages, because of high operational cost and the second solution will reduce the flow area in the tubing. Annulus Oil Based Mud Circulation is the latest solution implemented in the Handil Field, which utilizes the existing annulus to perform gas injection and then followed by the installation of Gas Lift Pack Off (GLPO) or Siphon String. This work begins with tubing punch at a depth where the gas lift injection point will be used, then proceeds to circulate OBM from the annulus to the waste tank, then followed by installation of GLPO or siphon string. This method has advantages, there are no heavy workover is required, no additional spool is needed on the tubing hanger for gas injection, and has a faster work duration compared to the two previous methods. Through this method, out of a total of 11 tubing less wells, there is a remaining stake of 1200 kbbls in the oil reservoir which has been successfully unlocked and some have been produced through this method and lifts with gas lift deepening, and there is still a remaining stake of 746 kbbls as a future candidate to be generated through the application of the OBM Annulus circulation method. This method is particularly applicable to old oil fields where there is residual oil-based mud in the annulus of several depleted gas wells and there are still oil layers that need to be saved.
Sand Erosion and Deposition Risk Mapping Using Network Model: A Case Example from Offshore Malaysia
Authors: Zin Zulkifli , Tg Aziz Tg Zulfadzly , Chee Ivan Xianlung , Tn Mahmud Tn M Yusoff , Tham Kah Meng
Published: October 2023

Flowline erosion due to sand production is a common occurrence in oilfield environment, causing Loss of Primary Containment (LOPC), resulting in substantial economic, environment and reputation damage to operators. To be proactive in monitoring flowline erosion, operators periodically conduct Ultrasonic Thickness Gauge (UTTG) across expected erosion and corrosion hotspots such as at flowline bends and tees. Despite the efforts put in the monitoring activities, LOPC still occur which often attributed to prioritized monitoring due to UTTG backlogs where single flowline can have at least 100 monitoring points, coupled with inconsistency or errors when conducting UTTG.

With the goal to identify sand erosion and deposition locations in the production system, a detailed network hydraulic model was developed with flowline dimensions and fittings arrangement based on isometric drawing and flowing conditions matched to latest well parameters. The hydraulic network model output for each flowline segment was then used to calculate sand erosion rate and critical velocity for sand transport using models available in the industry.

Using this approach, high sand erosion and deposition risk locations were identified at the current flowing conditions. Additionally, sensitivity analysis was performed to assess the effect of various parameters such as production rates, sand rates and sand size. The identified sand erosion and deposition risk hot spots were then included in the UTTG plan for further monitoring.

This paper will share the process of sand erosion and deposition risk mapping along the production system including data requirements, modelling workflow and results analysis. The approach can be replicated in other fields facing similar issues of LOPC due to sand erosion.
Unlocking Conditioning Monitoring Platform Through Implementation Digital Enablement Platform to Ensure Equipment Availability and Flawless Operations
Authors: Zuhruffani Risnu , Rahman Faisol Amri , Rokhmad Iqbal Faishal
Published: October 2023

Equipment health and monitoring platform is critical to ensure condition monitoring program for rotating machinery equipment which generates flow energy to transfer hydrocarbons for production and well injection, generates power for processing plant needs and waste disposal purposes. EHMS platform has been implemented in EMCL as part of machinery protection system and not being used to mitigate risk of some bad actors.

Unlocking EHMS platform that has capability to provide Early warning system with features avoid unexpected downtime, continuous vibration analysis, automatically notify users of abnormal condition, and Failure identification with features such as Vibration Trend, Axial Position, Phase Trend, Frequency Spectrum, Orbit + Time Waveform, Probe Gap Voltage and Shaft Centerline while steady state. Furthermore, EHMS also provide analysis in transient State with Polar Plots, Bode Plots, Cascade Plot and Spectrum Waterfall. It has challenges to enable accessibility on the EHMS platform in real time is challenging for EMCL, because the dynamic vibration data has high frequency of data (more than >1HZ), so it caused analysis and workflow only can be done thru those platforms cannot be done thru existing OPC data communication. Meanwhile the platform only available within isolated environment in Industrial control system, as we may know exposing those environments is very restricted due to some requirement and has cyber risk.

It does require strategic technology architecture deployment at scale that enable secured remote capability with compliance with IEC 62443, complex mitigation is implemented, put control point in place is needed to manage the risk and business value creation after implementation.

The architecture and design should be able to accommodate expansion of future control system topology that able to capture another operations process automation.

With implementation of digital enablement platform has provided benefit for conditioning monitoring technique to identify early failure indication through spectrum analysis in regular basis, detect for any misalignment thru band-alarm enablement, provide accurate and deep analysis while executing during on-site balancing on GTG, and minimized downtime in injection compressor to reduce flare rate.
Probabilistic Study on Gaslift Compressor Mapping with Network Modelling - How to Stabilize Gaslift Distribution and Optimise Overall Production with the Optimum Gaslift Compressor Combination?
Authors: Polycarp Maurice Anak , Chaw Kit Teng
Published: October 2023

Field X is a mature brownfield with aging facilities and relies heavily on gas lift as artificial lift. Field X runs gas lift compressors with a 4+1 operating philosophy. However, significant unplanned deferment up to 12% is associated with the gas lift compressors due to frequent tripping events (cascaded from high suction pressure). Historical data also shows that certain combinations of the gas lift compressors are more sustainable for better uptime and result in better overall production. This study aims to utilize GAP to execute a probabilistic study to investigate the relationship between compressor combination and the spread of gas suction across the different units, and to develop ideal compressor combinations for Operation's reference.

GAP is used to model the process layout of the five gas lift compressor units. Next, multiple sets/permutations of suction pressure configurations are used to run network solving iterations to estimate gas suction into each compressor. This is done for three scenarios i.e., when 2/3/4 gas lift compressors are operating concurrently. Subsequently, comparison is done on the standard deviation of each set of data (gas distribution across units) for each combination. This can also be done in graphical format via plotting of normal distribution graphs. For each scenario, the aim is to identify which compressor combinations result in relatively lower standard deviation, which means relatively uniform gas distribution across units and lower chances of unit tripping due to high suction pressure.

This study has developed a ranking of gas lift compressor combinations, subject to the number of units operating concurrently. This ranking is cascaded to Operation for reference when operating the compressors. This ranking is also mapped against production data (historical and moving forward). It shows that the combinations, with lower standard deviation outcome from the probabilistic study, do result in more stable gross production and water cut. Additionally, higher-ranked compressor combinations also demonstrate healthier discharge pressure (>650 psig) compared to that of lower-ranked (600 psig). Comparison of field production data, between periods of higher-ranked compressor combination and those of lower-ranked, shows instantaneous gain of 1000 bopd. This is due to higher GLC discharge pressure, higher compressor uptime and better stability.

This paper will describe the integration between subsurface and surface to identify the optimum gas lift compressor combination to deliver a sustainable gas lift supply, and to ensure higher uptime of the compressors, while optimizing overall production. This analysis will be coupled with subsurface understanding on well line-up optimization to maximize gain.
A Surrogate Model for Numerical Reservoir Simulation of CO2 Flooding and Storage Based on Deep Learning
Authors: Dong Peng , Liao Xinwei , Zhang Lingfeng , Zhang Heng , Zhao Xurong , Xue Qishan
Published: October 2023

Numerical simulation is an important tool for CO2 flooding and storage simulation, which allows to obtain global approximate solutions of governing equation. However, the simulations often suffer from significant computational costs and convergence problems, especially considering the pseudo-component and CO2 storage mechanisms. This makes the scheme optimization tedious. Therefore, we propose a deep learning-based surrogate model to efficiently implement numerical simulation of CO2-flooding and storage. Proposed method consists of automatic encoder and prediction part. The auto-encoder consists of VQ-VAE model, which projects the reservoir's 3D properties into 2D space. The prediction part consists of ConvLSTM models, which accepts reservoir variables. Finally, the surrogate model outputs the dynamic characteristics of production and different CO2 storage forms. The results show that the original reservoir properties can be restored with high fidelity after autoencoder training. The correlation coefficient between the decoded attribute and the original attribute is greater than 0.98. For prediction part, ConvLSTM can accurately predict the dynamic characteristics of production and different CO2 storage forms. The average relative errors of the predictions in the training and validation sets were 4.37% as well as 8.91%. In addition, for computational efficiency, the surrogate model is two orders of magnitude faster than the numerical model. It is proved that the surrogate model can effectively replace the numerical simulation model and greatly improve the computational efficiency.
An Industry Game Changer Approach in Managing Medium-High Complexity of Well via Robust Risk & Reward Contract Strategy – A Win-Win Concept for Both Operators & Service Providers
Authors: Mohd Mokhtar Mohd Khaidir Bin , A Kadir Norazan Bin , Hamzah Nurul Ezalina Binti , Xiong Choi Yee , Yahaya Fadzil Bin , W Othman W M Safwan Bin , Md Saleh Siti Noor Asheiah Binti , Leong Chua Hing , Khairul Anuar Khairina Binti , Amsidom Amirul Adha Bin , Harun Raihan Bin , Nordin Azri Bin
Published: October 2023

The efficient and successful execution of oil and gas well projects are critical for companies operating in this industry. However, the conventional contract model, where operators company bear the entire economic and operational risk, has proven to be a deterrent in executing medium to high complexity wells. This manuscript explores a risk & reward contract strategy as an alternative approach to overcome the limitations of conventional contracts. The risk & reward model promotes risk sharing between the operator company and service providers, offering incentives for successful operations while mitigating the impact of failures. This manuscript discusses the benefits, challenges, and implementation considerations associated with adopting risk & reward contracts in the oil and gas industry.
Reservoir Management Integration of Asset Development and Asset Optimization Aspect in Managing DSF Field New Area Steam Flood Project
Authors: Nuruddin Mukhammad , Aji Muhamad , Pradana Candra Arya , Raharja Sulastama
Published: October 2023

DSF Area 13 is the newest steam flood project that has developed about 800 acres area, utilizing over 350 oil producers and 145 steam injectors at initial development. Steam injection optimization is quite challenging due to poor lateral connectivity and lower reservoir quality; hence the area was behaving with poor steam flood response. A reservoir management integration and effort are introduced in 2021 to improve overall area steam flood performance.

Method includes continues improvement on the Reservoir Management Strategy which integrates new development and optimization of the current asset. The integrated effort consists of geological new conceptual model development, new development well strategy, injection strategy updates, and drainage process improvement at existing wells. Those efforts are grounded by steam flood life cycle knowledge in gravity drainage model and aimed to improve steam chest progression which was slow before due to poor reservoir. The uniqueness of the area demands those efforts to be dependently executed and requires holistic reservoir management.

A geological new conceptual model reveals that the area has various geological characteristics which correspond to production-injection performance. New infill wells show massive bypass oil which is not expected at 7+ years steam flooded area. It also enables steam injection optimization by improving pressure depletion and lateral connectivity. It impacts faster heat maturity and furthermore will enable faster heat management and faster oil recovery simultaneously. Injection strategy update results to three difference approaches of steam injection. Conventional steam-increased strategy is applied to medium connectivity pattern and is aimed to accelerate breakthrough time. Revisiting injection is applied at high pressure pattern and will be executing through staging approach. Theoretical heat requirement is re-evaluated at pattern which has new infill wells to achieve production-injection alignment. Existing producer well is optimized by performing pump optimization, acidizing job campaign, and steam cyclic stimulation resulting in good production response and impact to improved reservoir pressure depletion in the high-pressure pattern. As a result, in area level, oil production shows an inclining trend which is not expected from the last 2-3 years’ forecast, adding more than 7.7 MMSTB reserves from previous year's booking.

This paper explains all efforts related to reservoir management to improve the performance of this new steam flood project from both optimization and development aspect. It explains how to demonstrate reservoir management at particular asset and ultimately to turn a poor steam flood area into an inclining trend. Hopefully it can be adopted to another area/ field which is experiencing the same poor steam flood performance.
Advancing Well and Remote Compressor Performance Through Data Analytics
Authors: Kongkiatpaiboon Suradech , Laosuwan Sarita , Tangsawanich Yuranan , Sopitviriyaporn Chain , Parimontonsakul Monthep , Kaivalkritiyakul Polake , Payaksiri Siriwan
Published: October 2023

Optimizing wells and remote compressors for operations can be time-consuming and hard work. Engineers and operation team struggle to uncover system bottlenecks and modify operating parameters. To automate the traditional optimization procedure, a novel data analytics workflow was applied alongside compressor simulation data. In this research, an innovative framework for optimizing facilities equipment has been adopted in this project to increase the value of assets via increased productivity.

The results of thousands of compressor simulation runs have been exported to a training database. The system's operational data in real-time has been mapped to simulation findings using a data science model. Optimization workflow for different kinds of problems has been speculated up and made. This process is integrated using cloud service and machine learning deployment environment to generate a database of recommendations. The bottlenecks in the system are then visualized using an interactive dashboard, which acts to eliminate the bottlenecks during normal system operation. With an R2 greater than 0.99, the data science model matches the simulation findings well. After a few sessions of brainstorming with specialists, the optimization method covers practically all operational restrictions. This environment is being used to deliver daily analysis and recommendations to the operations and engineering teams.

With the new framework, the traditional well and compressor optimization process has been transformed to a cutting-edge digital solution. The time required to locate wells and compressor bottlenecks has been significantly reduced. Opportunities that were previously not visible owing to inadequate time for workers to look at in the old approach have now been captured, and offshore adjustments have been completed much quicker than the prior approach. As a consequence, this initiative has the potential to provide large productivity gains. Furthermore, the analytical findings will serve as the basis for following facility optimization. Problems with wells and compressor packages will be identified as system constraints and used as input characteristics to anticipate downstream equipment failure or analyze troublesome wells to choke down. This project will provide a data foundation for other topside facilities in the future.

In summary, this study has pioneered a new, automated approach by bringing together operation, machinery domain, and data science experts, which allows for delivery of effective bottleneck identification and recommendation to enhance well and compressor performance. In the future, this will serve as the basis for an automated workflow and a digital twin of the facilities, both of which will improve the oil and gas industry's ability to manage the efficiency of its wells and compressors.
Environmentally Friendly CO2 Resistance Cement for Carbon Capture Storage Project: First Deployment in Offshore Malaysia
Authors: Riyanto Latief , Kumar Avinash Kishore , Shahril Muhammad Afiq , Lau Chee Hen , Sazali Yon Azwa , Amir Muhammad Syafeeq Ebining , Jain Bipin , Kapoor Saurabh , Yakovlev Andrey , Duong Anh Tuan , Chong Woon Phin , Medvedev Anatoly
Published: October 2023

Geopolymer cement technology was developed as alternative cement system that can withstand harsh acidic environment normally encountered in Carbon Capture Storage (CCS) fields or high CO2 gas fields. It is also environmentally friendly technology as the processes converts fly ash (waste from coal-fired power plant) into construction material. Following a successful yard test in 2021, it was agreed to validate the new technology by piloting in offshore well. The objective is to check the operational feasibility in offshore environment. The paper aims to describe the whole process starting from candidate screening, job design, operation, and evaluation of the pilot.
Ocean Sheen Caused by Complex of Solids, Micro Asphalts, and Iron - Investigation and Solution
Authors: Franca Leonardo , Fakunle Daniel , Da Silva Danilo
Published: October 2023

This work was done to propose a list of alternative water clarifiers. Discoloration (Sheen) was observed in sea water due to impact of overboard produced water quality and one of the causes is the type of clarifier being implemented (i.e., DTC - Dithiocarbamate), which will be replaced to a non-DTC. After this new chemical is implemented, a reassessment of the overboard produced water quality will be carried out to understand if there is the need to improve this water quality.

The included the following requirements as:

Improve the visual water aspect (ocean surface). Improve the water quality. Root cause investigation.

The potential causes of the sea water discoloration include:

Iron oxidation which is iron exposed to oxygen in the sea surface (20 to 50 ppm of iron is presented in the produced water going to the sea). Poor chemical treatment performance. Presence of Water-Soluble Organics (WSO). Presence of solids.

At the conclusion of the water clarification product selection test, the following observations were made:

A combination of 20 ppm of Coagulant A followed by 20 ppm of Flocculant D performed excellent, reducing the oil in water content from 36 ppm to 2.0 ppm after five minutes of residence time but with instantaneous action and separation (oil/solids and water). This combination was the best/first choice. A combination of 40 ppm of Water Clarifier C followed by 20 ppm of Flocculant D reduced the oil in water content from 36 ppm to 7.0 ppm after five minutes of residence time. 100ppm of Scale Remover E or Scale Remover F to treat Slop water. This recommendation helps to improve flow back from Slop tanks or cargo tanks with water from those vessels. Usually Slop water present many solids and iron content. Both products were tested against a Slop water/produced water combined.
Multiphase Flow Diagnostics for Evaluating Gas Shut-Off Performance to Minimize Carbon Footprint
Authors: Ravichandran Tenamutha , Sidek Sulaiman , Giniyatullin Artur , Abdul Latif Azzad Hafiz
Published: October 2023

This paper discusses the results of a flow diagnostics survey conducted to evaluate the performance of a Gas Shut-Off (GSO) campaign in Field A. The field faced challenges associated with a high Gas-Oil-Ratio (GOR) production, leading to excessive carbon emissions, reduced field production efficiency, and elevated carbon-per-barrel rates. Additionally, the presence of excess gas not only consumed valuable pipeline ullage but also caused transportation and flow assurance issues. Total field gas production had already exceeded the limit of surface processing facilities, which meant the Operator had to choke back production. Managing and processing excess gas in Field A requires substantial effort and capital expenditure for surface infrastructure and facilities.

The GSO campaign involved the installation of a 200 ft long 2-7/8 in. tubing straddle to effectively isolate the zones with the highest gas contribution. The identified well, DW#2, was a 7 in. × 4-1/2 in. cemented monobore across several commingled oil and gas-bearing zones. The well consists of five (5) clastic reservoir zones, each with multiple layers, all of which are perforated over an extensive interval exceeding 1,500 ft. This configuration poses significant challenges in accurately determining production allocation, addressing flow assurance issues, understanding reservoir connectivity, monitoring well performance, and forecasting total field production. In addition, the high degree of complexity meant that standard production logging methods could not accurately characterize flow or confidently distinguish the main gas-contributing layers.

Through the flow diagnostics survey, the paper evaluates the success of the GSO campaign in mitigating the high GOR production challenges and improving the field's performance. This paper aims to contribute to the broader understanding of managing excessive gas production in complex reservoir systems while striving to achieve enhanced field productivity and environmental responsibility.
Basic Sediment and Water (BSW) Artificial Intelligence Integration in Heavy Oil Steam Flood Central Gathering Station Facilities Through Machine Learning Regression Model Implementation
Authors: Jati Pandu Prabowo , Santoso Ade Anggi Naluriawan , Sani Ahmad Nurkholis , Kumar Muhammad Phanterektus
Published: October 2023

The Delta field, once at its peak production in 1992 with 290,000 barrels of oil per day and a daily steam flood injection of 1 million barrels, is now experiencing a significant decline in production. Operational challenges persist and are compounded by the complex integrated facility system in the Delta Field. These challenges include production measurement, treatment, steam generation, steam distribution injection, water disposal, and injection network. Dynamic operations involving steam distribution and well stimulation activities lead to fluctuations and changes in temperature-fluid characteristics. Moreover, the treatment of heavy oil from the Delta Field is difficult due to its high viscosity and the presence of emulsion stabilizers such as asphaltenes, organic acids, and generated sand.

Managing BSW (Basic Sediment & Water) has become increasingly challenging due to the complexity of operations and the extended production period of over 30 years since peak production. To address this, a BSW prediction tool was developed, utilizing existing data infrastructure to enhance processing facilities’ ability to manage BSW more effectively compared to previous practices. Previously, operators could only respond to increased BSW levels without an online prediction tool. The developed tool utilizes AI (Artificial Intelligence) and Data Science (DS) models to predict BS&W values with a remarkable R2 value of 0.945. However, challenges arise during data integration and preparation, including data supply for model training, data acquisition techniques, and measurement capabilities. Fortunately, the final DS/AI Model can provide an early warning up to 2 days before potential BSW upsets, improving safety performance in treating high-risk steam systems by enabling prompt decision-making, reducing errors, and increasing efficiency. As a result, the average percentage of BSW upset cases per year has significantly decreased from 15.08% to 1.05%. Overall, the application of this technology has led to improved management of BS&W.

In this paper, we will present an overview of recent collaborative initiatives that utilize data science and machine learning-artificial intelligence as an alternative solution to address the challenges related to BSW quality in the crude oil process separation of Indonesia's steam flood operation in the Delta Field. The project team's findings suggest that the adoption of DS-AI holds great promise in unlocking additional optimization opportunities in oil and gas processing, capitalizing on the vast and expanding dataset available.
Data-Driven Production Forecasting for Shale Gas Wells Using Production Characteristics Analysis
Authors: Shin Hyo-Jin , Lim Jong-Se
Published: October 2023

Several studies have used machine learning-based techniques to improve the production behavior prediction in existing shale gas wells. However, few studies have investigated production prediction in new wells wherein no prior information is available. This is challenging because these predictions are generally based on the analysis of data available on existing wells. Therefore, in this study, data-driven analytics is utilized to analyze the production characteristics of existing wells and improve the predictive performance of the production for new wells.

Field data on the Marcellus Shale wells with production histories exceeding 48 months were collected from Enverus’ Drillinginfo. We derived production-related attributes of these wells and identified the key factors using principal component analysis to establish the production dependency on them. Subsequently, the prediction reliability was improved by classifying different production characteristics into groups, and using their trend lines to estimate the cumulative production of the existing wells. For new wells, we developed a model to classify groups based on key factors, and utilized probabilistic values from the classified groups to predict stochastic ranges of cumulative production using an artificial neural network.

The field data were normalized with respect to lateral length or the number of stages to enable comparison between multiple wells. Outliers of each input factor were excluded during pre-processing. An analysis of production characteristics was performed by classifying the existing wells into three groups. Results indicated that Group 2 was highly productive, with evident influence of normalized fluid volume during the middle and late phases of production. Further, initial variations in production tendency were observed in Groups 1 and 3 by spacing. Trend lines of classified groups were used to forecast the cumulative production per unit length (NP) of the existing wells. The observed error was less than 10 % in the prediction of NP 48 based on the analysis of NP 6 and NP 12. Additionally, high production variability in shale play is known to induce a rapid reduction in the production trend after the initial production. Therefore, a prediction model with NP of 6, 12, and 48 months was developed. To validate the model, probabilistic values of spacing and decline factors were used in the predictions of NP 6, 12, and 48, yielding an accuracy exceeding 80% and an error of approximately 10%.

The proposed multi-well productivity analysis is a trial-and-error process based on data-driven analytics, which can be used to predict shale production in any shale play. In addition, the range of the predicted probabilistic production includes the actual values; therefore, the prediction errors are small compared to those of previous methods for new wells. Consequently, time and resources expended for data acquisition are reduced, and the reliability of productivity forecasts in shale development is improved.
Fortifying Upstream Data Governance - Establishing Centralised Data Governance and Assurance Control Tower
Authors: Zait Nurshazareena Shuhada , Mohamed Ghazali Muhammad Azmir , Lee Hin Wong , Mat Ghani Normanisah , Nur Ismail Nur Aliah , Zakaria Zulhanizam , Mohamad Isa Mohamad Haneef , Azaman Dzulkarnain
Published: October 2023

PETRONAS Upstream is moving towards becoming a data driven organization. In order to ensure Upstream decision making is driven by trusted data, it is imperative to fortify Upstream data governance with structured and guided process and procedure, technique and methodology that define, build and operate data management knowledge areas as per DAMA DMBOK.

An innovative concept of establishing Data Control Tower as centralized data governance and assurance was designed and implemented to ensure that PETRONAS Upstream Data Governance is managed at the highest level with the following objectives:

Guardrail Upstream data standardization and consistency Oversight of data management activities Centralized data mastering Data quality performance monitoring Data catalog, business glossary and metadata management Data security control
Implementation of Recompletion Using Heavy Workover Unit 340 Klbs Unit to Solve Well Integrity Problem in New Oil Well: A Success Story and Lesson Learnt from Handil Field
Authors: Li Ulinnuha Iftitahul Lu'ayyi , Umar Arsalan , Suhartanto Andrian , Alyasa Muhamad , Maulana Muhammad Irfan , Wijaya Geraldie Lukman , Maz Nasuto Saidana , Setiawan Dedy , Wardhana Rahadyan Kusuma , Risal Miftachul , Jamal Muhammad Nadrul , Pradana Theodorus Aditya , Suwito Edy , Hidayat Mas'un , Setiadi Rahman
Published: October 2023

Well X is an oil well which was completed using the Mono Trip Gas Lift Completion (MTGL) in July 2019. Downhole safety valve (DHSV) problem observed since first well intervention performed on this well. From downhole camera running, it was observed DHSV's flapper was detached. To overcome this problem, a 2.3" Insert Pipe was installed transversely at the depth of the TRSV and ambient safety valve was utilized to replace the function of DHSV in order to allow the well to be produced. Due to the presence of 2.3" Insert Pipe and Ambient Valve, well intervention activities in this well were more difficult, longer duration due to more step, and had high potential for stuck. There are several unopened reservoirs in this well which still have a potential of around 235 kbbls of oil and 0.23 BCF of gas. After considering several options such as drilling a new well; perform recompletion with the rig; and rig less recompletion, this well was recompleted using HWU 340 Klbs unit. The job was carried out by cutting the tubing to a depth below side pocket mandrel depth, then installing a new upper completion with TRSV and some new side pocket mandrel additions. Tubing Swallowed Bell Guide Assembly is used as a connector between the existing completion and the new upper completion, then continued with the annulus cementing job. Through this innovation, the job can be completed within 17 days and total cost less than 700 kUSD, which resulted in savings up to 2 MMUSD when compared to drilling a new well, and succeeded in opening better access to the reservoir with a total value of up to 20.4 MMUSD.
Rapid Simulation and Optimization of Geological CO2 Sequestration Using Coarse Grid Network Model
Authors: Aslam Billal , Yan Bicheng , Tariq Zeeshan , Krogstad Stein , Lie Knut-Andreas
Published: October 2023

Large-scale CO2 injection for geo-sequestration in deep saline aquifers can significantly increase reservoir pressure, which, if not appropriately managed, can lead to potential environmental risk. Brine extraction from the aquifer has been proposed as a method to control the reservoir pressure and increase storage capacity. However, iterative optimization of the well controls for this scenario using high-resolution dynamic simulation models can be computationally expensive.

In this paper, we demonstrate the application of a so-called coarse–grid network model (CGNet) as a reduced-order model for efficient simulation and optimization of CO2 sequestration with brine extraction. As a proxy, CGNet is configured by aggressively coarsening the fine-scale grid and then tuning the parameters of the associated simulation graph (transmissibility, pore volumes, well indices, and relative permeability endpoints) by minimizing the mismatch of well-response data (rates, bottom-hole pressure) and saturation distribution from the fine-scale model. Calibration and optimization procedures are automated using gradient-based optimization methods that leverage automatic differentiation capabilities in the reservoir simulator in the same way backpropagation methods are used in training neural networks. Once calibrated, CGNet is employed for well-control optimization. Validation with the fine-scale model shows that CGNet closely matches the optimized net-present value (NPV). Numerical examples using the Johansen model, available as a public dataset, shows that the optimization can be accelerated up to seven times using CGNet compared with a fine-scale model. (Using a compiled language will likely result in significantly larger speedups as small models suffer from a disproportionately high computational overhead when executed in MATLAB.) This study implies that a reduced-order model such as CGNet can be a powerful data-driven tool for faster evaluation of CO2 geo-sequestration simulation, combined with proper reservoir monitoring program.
Alternative Solution for Deepwater Shallow Flow Hazard: Case Study from Shell Deepwater Project
Authors: Hoe Yijing , Heu Tieng Soon , Lee Shan Yik , Mohd-Radzi Razif , Yeap Fabian , Edwards Joseph , Charan Suri Chitra , Lo Rex
Published: October 2023

Gas bubbling was observed immediately post top-hole riserless cementation from the subsea conductor and wellhead in Field-A deepwater wells in Phase-1 and Phase-2 development campaigns. This has led to continuous underwater ROV monitoring and gas sampling requirement for structural integrity assessment. Foam cementing was considered but deemed impractical due to high logistical cost and limited regional experience. Conventional gas-tight cement with complex cement blend were attempted in another deepwater campaign with similar challenge but yielded inconclusive results.

Traditionally used to remedying lost circulation, thixotropic cement is a cement system where gel strength develops rapidly under static condition. In this case study, the thixotropic property was combined with shortened transition time properties to create a formulation that exhibits both aggressive gel strength development and a quick critical gel strength period post cement placement. However, pumping such cement system in big volume presented inherent risks where cement could prematurely gel up and harden in surface lines. This can potentially lead to CLIP, and in more severe cases, even total well loss. Comprehensive risk assessment including slurry design, sensitivity testing, quality control, and field trial were conducted prior to the execution. Saturated brine-based drilling fluid was utilized during drilling operations to enhance shale inhibition and prevent hole washout.

No bubbling was observed in all four wells in campaign after the cementation with thixotropic gas-tight system. Early planning and testing allowed for the successful implementation of this new cement system despite logistical challenges caused by the Covid-19 pandemic. Cement trial mix played a key role for the crew to understand the slurry behavior and access the equipment readiness. The outcome of this case study presents a promising solution for mitigating shallow flow hazard especially in Asia Pacific region where foam cement is not easily accessible.
Assessment of Field-Scale Geomechanical Risks Associated to Carbonate Reservoir Production in South Senoro Field
Authors: Younessi Ahmadreza , Sagita Romi , Mikhael Chrislianto Reynaldi , Laya Krishna Pratama , Helbet Ricky , Khawarizmy Atha
Published: October 2023

Senoro is a carbonate gas field in Banggai basin in Eastern Indonesian, an area with active collision margin. A comprehensive field-scale study is carried out to investigate the potential geomechanical related risks associated to the field production for the entire life of the Southern part of Senoro field. Well-centric geomechanical models were built for the exploration and appraisal wells in the South Senoro field. A robust field-scale geomechanical model is built for the area of interest which covers the entire South Senoro field. This is done by propagating the well-centric geomechanical model properties and parameters in the field-scale model using geostatistical approach tied with seismic attributed. Using a finite element approach, the model is then coupled with the reservoir flow dynamic model and simulated for the entire life of the field. The simulation results were used to assess the field-scale geomechanical related risks associated to production. The changes in stresses, strains and displacement induced by the carbonate reservoir depletion are obtained over the entire model at the end of each geomechanical simulation step. These are used to conduct detailed geomechanical analyses over the life of the field. The results shows that a stress path of approximately 0.69 is expected in the carbonate reservoir. This is while the stress changes in the caprock layer is relatively lower, and as expected, with a reverse trend. This is mainly because the reservoir compaction is relatively low with a maximum of 0.13% after 2,500 psi reservoir depletion. Subsequently, the maximum surface subsidence is also insignificant with less than 0.12 meters. Since the stresses within the caprock tend to slightly increase by production, the risk of tensile failure reduces over time. The risk of shear failure in the caprock appears to be negligible. The fault tau-ratio seems to increase only in the carbonate reservoir. However, it does not exceed more than 0.60 which indicates a stable state for the fault surfaces. Overall, the results show that there is no risk associated to compaction, surface subsidence, stability of the faults and caprock layer for the entire life of South Senoro field. The comprehensive workflow used to carry out the study covers all the geomechanical aspect of the risks associated to producing from South Senoro field which is essential to optimize the development plan and design of the surface and subsurface facilities.