bluuebunny/crossref_metadata_2025 huggingface dataset:
Advanced Prediction of Sand Production Onset Using Data Analysis and Machine Learning Techniques: Insights from Adriatic Sea Gas Wells
Authors: Nguyen S. , Gabry M. Adel , Soliman M. Y. , Myers M. , Ayman A.
Published: October 2024

This study revisits the field observations of sand production of gas wells in the Adriatic Sea to develop comprehensive correlations of key parameters and identify the most critical factors influencing the onset of sand production. The primary objective is to leverage profound data analysis and machine learning (ML) techniques to boost predictive consistency and provide actionable insights for sand-free production practices.

The research employs a two-pronged approach. First, a detailed data analysis is conducted, featuring vivid cross plots to illustrate relationships between cohesion strength and various parameters such as depth, interval transit time, cohesion strength, original static reservoir pressure, effective overburden stress, depleted pressure, total drawdown pressure, perforation interval, shot per foot, and produced gas and water rates. Second, the study applies ML models, including Gradient Boosting (GB), XGBoost (XGB), Random Forest (RF), CatBoost (CATB), and Support Vector Machine (SVM), to categorize data and identify the most critical features impacting sand production onset. SMOTE is utilized to rectify class imbalance, and GridSearchCV optimizes model parameters. Additionally, LOOCV is employed for rigorous model evaluation. SHAP analysis further interprets the model results.

The cross plots reveal significant relationships between cohesion strength and other essential metrics, providing thorough knowledge of their interactions. In the ML classification phase, the GB model achieves a perfect accuracy of 1.0, significantly outperforming XGB (0.86), RF (0.71), and CATB and SVM (both 0.57). The GB, XGB, and RF models identify critical features such as interval transit time, cohesion strength, and water production as major influencers on the onset of produced sand. SHAP analysis further elucidates the contribution of these features, offering interpretable insights into their importance. The findings suggest that ML models, particularly GB, can effectively predict sand dislodgement, thus aiding in developing sand production preventive strategies.

This paper introduces an alternative application of ML techniques to foresee sand production onset, an essential challenge in oil and gas well management. The study provides new insights and enhances predictive accuracy by integrating extensive data categorization with advanced classification models. The use of LOOCV ensures rigorous model evaluation, and SHAP analysis for model interpretation offers a transparent understanding of feature importance, making the findings highly valuable for sand control approaches. This research contributes additive information to the existing literature, emphasizing the potential of data-driven approaches in improving operational decisions in long-term production.
Integrated Reservoir Evaluation and Simulation Study of the Northeast Alamein Field: A Field Case Study
Authors: Ubani Ephraim , Shahsavari Darius , Duruewuru Lester
Published: October 2024

The Northeast Alamein (NEAL) field, discovered in August 2010 with the drilling of NEAL-1X well, is an integral part of the Yidma-Alamein concession in the Western Desert of Egypt and is located about 3 km to the northeast direction from the Alamein oil field. Eighteen wells, a mix of vertical and horizontal, have been drilled in the field. The NEAL field is one of the primary oil producers of the concession and of the estimated 42.7 MMSTB of OOIP, the current recovery factor is about 12.0 percent. The objective of the study of the NEAL field was to develop a better understanding of the field comprising seven main complex reservoir members (A/R "E" sands, Upper A/R "G", A/R "G" Dolomite, Upper Bahariya, Middle Bahariya, Basal Middle Bahariya and Razzak sands), assess the production pattern of each reservoir and recommend an optimum production plan based on the ultimate oil recovery and economics.

The study involved the reservoir characterization of the reservoirs, which spanned seismic evaluation, petrophysical evaluation, facies modeling, and stochastic reservoir parameter distribution, culminating in static model development. All available engineering and production data were integrated with the static model to develop a representative model of the NEAL reservoirs, which were applied to derive future development plans.

The Upper A/R "G" and A/R "G" Dolomite reservoirs are most probably deposited in shallow marine from outer subtidal to intertidal zone, while the tidal flat depositional setting is proposed for the Bahariya and the Razzak units. Recommended optimum production plan involved a combination of infill drilling, well recompletions, pump optimization, and water injection.

The results of implementation of recommendations exhibit success in terms of additional reserves, of about 2.0 MMSTBO, and doubling production rate from the NEAL field. Lead tasks for water injection were completed with drilling of two water source wells and conversion of two wells for water injection. Water injection started in one of the wells on August 7, 2024. The offset producers are being monitored.

Integrated reservoir study in support of reservoir management of a mature field has led to successful drilling, recompletion, artificial lift optimization and other workover campaigns, which have yielded significant production optimization and reserves addition, as well as expected good performance of a waterflood project.
Maximizing Profitability through Automated Production Optimization: A Game-Changer for Digital Oil Field Operations in Kuwait Integrated Digital Field
Authors: Al-Rashidi H. , Singh Sahil
Published: October 2024

The paper outlines a digital transformation of a business process called production optimization, which traditionally an approach of identifying wells in the asset as candidates for choke or artificial lift parameter change. Optimization takes into consideration reservoir guidelines and well and facility constraints. The business process impact multiple teams that are involved in order to increase or optimize well production for over 2000 producers on daily basis. The paper focuses on the automation of engineering workflows, reporting, and decision making, ticketing and tracking of each opportunity through KwIDF platform. It introduces model based approach in decisions making related to choke change, artificial lift optimization or rerouting of the wells, which was not traditionally followed while identifying optimization opportunity on daily basis. In the end all the action and decision related to each opportunity are recorded which can be utilized to provide feedback thereby improving effectiveness and efficiency of the workflows and business process in the future.

Multiple engineering workflows involved in the business process start from updating or creating well models automatically after new drill, workovers or rig-less activity. An automated well-model management system ensures data accuracy, transformation of the data and timeliness by fetching information from the production database. Another workflow updates well performance for each wells automatically based on the multi-rate well test data. In the end optimization workflow utilizes well models and identifies opportunities for improving well production or running ESP pump optimally based on artificial lift, well, reservoir and facility limits and constraints. This automated approach enhances the identification of valid optimization opportunities and facilitates well performance management, leading to significant oil production gains and informed decision-making within the field.
Evaluation of CO2 Storage Capacity Potentiality as a Secondary Driving Mechanism in Enhanced Oil Recovery in East Bahariya Field, Bahariya Concession, Western Desert, Egypt
Authors: Dahman Ahmed , Mohamd Hazem , El-Rahman Reda Abd , Ataallah Mohamed Abdelwahab
Published: October 2024

Egypt formulated its sustainable development strategy "Egypt Vision 2030" in 2015. This strategy aims to protect the environment in the development process by integrating environmental aspects into economic and social development plans to manage natural resources, conserve natural capital, and develop to protect the environmental rights of future generations. According to the IEA (International Energy Agency) CO2 emission reduction projects to track advances in carbon capture, utilization, storage as well as use of naturally occurring CO2 for EOR (Enhanced Oil Recovery) of depleted reservoirs. This paper proposes a methodology for evaluating underground CO2 storage capacity according to the facies of different formations applicable to the CO2 EOR projects. The methods proposed in this document will not only help third parties create reports and inventories of greenhouse gas emissions from companies, but also help governments to encourage companies to reduce their CO2 emissions. It would be beneficial for the industry implementing CCUS (Carbo Capture Utilize and Storage) projects to provide key evaluation parameters and implement the necessary monitoring techniques. Due to advantages and vast resource capacity, onshore CO2 storage provides an attractive option.

Bahariya concession is located at the eastern trough of Abu Gharadig basin, Western Desert, Egypt. By Using the available data, a subsurface geologic evaluation and 3D modelling was carried out in terms of thickness variation, lithofacies, structural setting and depositional environment of the studied rock unit in the encountered basin. This study presents both depleted reservoir and shallow non-reservoir formations as preliminary targets for CO2 storage potential.

It was concluded that both clastic and non-clastic Cretaceous formations have a high-quality potential geological reservoir repository for CO2 storage capacity.
Re-Access Oil Reserves of Watered Out Shut-In Well in Mature Field; Case Study in the Gulf of Suez
Authors: Falamouny Peter M. , Ibrahim Ahmad , Salah Muhammed , El-Sheikh Mahmoud , Khalil Ahmed , Ayyad Abdelhadi
Published: October 2024

Hilal field is a mature brown field in Gulf of Suez. The field was discovered in 1982 and started production in July 1984 from five reservoirs. The platform was damaged due to ship collision shut down in 2007. A new platform was installed and restarted production in 2014. This paper showed the integrated dynamic and static study conducted to define and restore the remaining reserves of old P&A watered out producer.

The study included reviewing wells/ reservoir production and pressure performance and all saturation and production logs to monitor water movement across the field and compare wells production performance in different reservoir compartments. New structure maps were built based on new seismic and geological interpretation and to match the dynamic information got the study. Review of the completion fluid during workovers was done to judge its effect on wells production performance. Water oil ration versus cumulative oil production curve was studied for all Nubia reservoir to define the general WOR trend and define remaining reserves of old wells.

Wells production performance and production logs showed that despite being in down dip location, WELL-5 was the only well Nubia reservoir producer when old platform was, while up dip wells were completely watered out. Structure map was updated based on information and new fault was added to isolate Well-5 block. Focusing on Well-5 as possible oil potential location, the well was completed as Nubia producer in 1985 became a commingle producer from Nubia and Nukhul S. St in 2000. The well was producing with 85% WC when P&A. Production logs run in 2002 showed that Nukhul was producing with 90% water cut and 60% of liquid rates. Well workovers history showed that Nubia reservoir was damaged due to completion fluid during workover in 1994 and productivity was decreased. This justifies the domination of Nukhul S. St on Nubia. WOR versus cum oil curves suggested that Hilal-A5 was producing 60-70 % WC from Nubia when the well was P&A and Nukhul S. St was watered out. Based on the study, Hilal-B6 well was drilled targeting Well-5 location. The well penetrated +250 ft oil column in Nubia. By selective perforation, the well started production with traces water cut from Nubia.

This paper showed the value of detailed integrated dynamic and static study. It showed workflow of studying the re-development of mature fields and finding sweet spot that can raise the field production.
Enhancing Oil Production Through Inclusive ESP Solutions
Authors: Alfaitouri I. , Awedan H. , EL-Dalim M. , Bosnina S. A. , AlKyarie S.
Published: October 2024

This paper introduces and evaluates the effectiveness of a comprehensive upgrade to the electrical submersible pump (ESP) systems implemented in Libya's Waha oil field, the country's most mature and giant oil field. This upgrade integrates advanced technologies across both downhole and surface components of the ESP systems, incorporating the latest digital ESP solutions tailored to meet customer operational requirements.

The paper details how this extensive enhancement in ESP design has significantly improved system efficiency and performance. By modernizing conventional ESP setups. The upgrade addressed the limitations of outdated ESP systems, enhanced ESP monitoring capabilities, and significantly boosted oil production in Waha field.
Success Story: Improving CBL Quality in Loss Circulation Conditions Using Low-Solids-Shear Dependent Cement System
Authors: Rachman Ryan Pratama , _ Sulistyo , Syarif Mustafa , Anuraga Edo , Daroni Afwan , Adrian Nur Alam Rifqi , Martin Ranti , Delgado Francisco
Published: October 2024

An operator onshore Indonesia performed a remedial squeeze cement operation to help improve the quality of the cement bond based on cement bond log (CBL) results. The 4.5-in. production casing, perforated between 1850 and 1852 m measured depth (MD), showed well instability with static losses at 0.7 bbl/min and dynamic losses at 1 to 1.18 bbl/min with minimum flow rates up to 3 bbl/min. Four conventional cement slurry squeeze operations failed to yield positive results in addressing the losses because all the cement was lost to the formation behind the casing no cement was tagged inside the casing across the perforated interval.

A low-solids-shear dependent (LSSD) cement system with a density of 11 lbm/gal was considered to address the challenge. This cement system reduced hydrostatic pressure above the loss zone and had tailored characteristics of early development of static gel strength. The 40-bbl treatment was pumped through an open-ended drillpipe (OEDP), with the annulus closed above the loss zone. Initially, 10 bbl were pumped to the formation, 30 bbl remained inside the casing, and 15 bbl were then squeezed behind the perforated interval using the hesitation squeeze method, followed by an eight-hour wait on cement (WOC).

After the completion of WOC, the well remained static, and cement was tagged 104 m above the perforated zone. No further static or dynamic losses occurred after the cement was drilled. A successful pressure test up to 1,000 psi was performed. The repeat CBL showed improved zonal isolation and a competent barrier between the zone of interest and the water zone, which enabled the operator to proceed with the completion program without any additional treatments.

The application of the LSSD cement system resolved losses on the first attempt, while four conventional cement slurry operations failed. Additionally, the LSSD cement system improved cement bond quality behind the production casing, which achieved the CBL result necessary for the operator to proceed with the well completion program.
Advanced Drilling Strategies and Zonal Isolation Techniques for High Temperature, High Pressure Wells, A Case Study
Authors: Presniakov Mikhail , De Souza Giovana , Lujan Juan Rodrigo , Barrera Edison , Ivanov Roman , Nunez Andres
Published: October 2024

This case study outlines the successful risk management through engineering in Mesozoic reservoir. The subject well is a High-Pressure High Temperature (HPHT) extended reach S-Shape. The primary objective of this paper is to detail the strategy applied to ensure well integrity, effective zonal isolation, and operational efficiency while mitigating risks associated with mud losses and crossflows. Scope will cover efficient isolation using a 5-in. liner × 6-1/8-in. open hole with a custom swellable packer; Validation the use of Managed Pressure Drilling (MPD) techniques and two-phase flow systems; minimization non-productive time (NPT) and operational costs.

Risk management strategy starts through offset wells analysis. General well design is affected by the presence of a series of folds and faults, as well as salt domes without a predetermined orientation. Therefore, the existence of significant uncertainty in pore pressure prediction. A safe execution depends on real time follow up through dynamic simulations and managed pressure drilling with advanced intelligent chokes. Whenever the combination of late and early Jurassic was confirmed, contingency scenario needs to be activated. This involves custom cement job in reduced annular clearance of 5-in. × 6-1/8-in. with fit for purpose packer and cement system. And finally, to explore the early Jurassic reservoir at depths from 7,400 m to 7,500 m true vertical depth (TVD) safe execution depends on managed pressure drilling (MPD) with continuous nitrogen injection and real time parameters correlation with dynamic simulations for drilling 4-1/8-in. section.

This strategy yielded several positive results. Good identification of the geo-body position through controlled influx management within 1.75 to 1.81 gr/cc using MPD equipment. Successful zonal isolation, through selection and deployment of a cement system and a swellable packer activated by oil-based mud, designed to operate up to 191 degrees Celsius (°C) and withstand differential pressure up to 10,000 psi. The well integrity was confirmed through negative test and further in production phase. The reservoir was successfully explored with minimal reservoir damage possible in subject conditions through the use of at balance two-phase flow to manage mud losses and maintain well control. Although at first, such target depths and high-pressure nature of the field may seem to be intimidating, the successful risk management and timely intervention to activate contingency has proven successful. The well achieved the planned technical limit time of 131 days, demonstrating this strategy's efficiency.
Rejuvenating Mature Field Production Through Optimized Artificial Lifting Methods
Authors: Mousa A. A. , Abdelazim A. , Youssef F. , Elkody M. , Farag N.
Published: October 2024

Marina oil production Company aiming to enhance oil recovery factor, which represents percentage of economically recoverable original oil in place by changing the artificial lift technology in the Sidi Rahman brownfield. Improving the recovery factor help increase the field's overall production and extend its productive life.

The Company has established a technical team consists of members from different disciplines. The team conducted a comprehensive study, re-evaluated the reservoir characteristics, original oil in place and remaining reserves in each reservoir sand, to maximize the recovery factor. To increase oil production, reduce operating costs, and evaluate new infill drilling opportunities. The main challenges that the wells encounter Multilayer reservoirs and the existing artificial lift system (Sucker Rod Pump) cannot establish higher draw down in high productivity index reservoirs due to the limitation of downhole pump size (through tubing pump, not bigger than 2.25") to allow zones with different reservoir pressure to contribute its production, despite the fluid level is near by the surface. Hence, it is decided to replace the existing Artificial lift method by an electrical submersible pump (ESP), to create a higher drawdown and increase production rate.

A work over campaign was successfully executed and converted the two sucker pump wells to produce by electrical submersible pumps. The results of ESP installation and commissioning were amazing and indicated a significant increase in Marina Company production from 130 to 1000 BOPD. Oil production increasing approximately by 660 % from company production prior the workover campaign, in addition to a significant decrease in operating cost from approximately 38 to 15 USD / bbl. oil through first year of implementation.

The new artificial lift method (ESP), successes in enhancing contribution from multiple zones with different reservoir pressures and contributed in increasing the recovery factor by 7 % during this period.
Evaluations of Productivity, Injectivity and Wellbore Integrity of Gas (CH4/CO2) Storage
Authors: Wang Yarlong
Published: October 2024

Gases such as CO2/CH4/H2 are injected, stored and produced later in high-permeability and large pore volume underground. With different thermal-hydraulic-mechanical characteristics at different depth, gas properties such as gas density and thermal conductivity may vary due to either formation pressure and temperature changes. Different injectivity/productivity and THM responses in vicinity of a wellbore at a given depth vary with depth. Consequently different critical pressures of wellbore integrity (fracturing/collapse) may be expected accordingly. An analytical solution of coupled HM model with a pressure- and depth-dependent fluid density corresponding to the formation thermal gradient is developed. Comparing to a typical gas flow, a supercritical pressure/temperature at different depth must be identified above these critical temperature/pressure the density change must be considered. Different mass productivity/injectivity may be obtained at each depth of the opensection, leading to a total different result from those utilized conventionally. Furthermore due to density-dependent effect, the changes in pore pressure, the corresponding gradient, and the effective stresses profile in vicinity of a wellbore may lead to a serious wellbore integrity issues such as hydraulic fracturing and critical wellbore collapse. We conclude that a density change over an order of 103 may be found for CH4/CO2 at the depth where critical pressure/temperature is surpassed. A wellbore solution with coupled THM model and non-linear diffusion equation for gaseous like CO2 is developed. Laplace transform technique is applied for the coupled solution. The induced pore pressure and stresses are calculated to determine the critical wellbore pressure and temperature at different depth for wellbore stability and undesired fracturing. We conclude density change under different depths may correspond to different tempo-spatial pressure and stress changes in vicinity of a wellbore, particularly when supercritical condition is reached. Such a density-dependent pressure and stress changes may lead to different wellbore collapse and fracturing pressures subject to a inflow or outflow conditions, respectively. Different injectivity and productivity in terms of mass flow may also obtained at different depths. Thus a depth-dependent critical pressure and temperature may be generated at different depths. A maximum/minimum wellbore pressures must be determined to balance the maximum injectivity/productivity and wellbore integrity, i.e. fracturing/collapsing.
Evaluation of Waterflooding Project Technical Viability in a Clastic Sandstone Reservoir: A Case Study in Western Desert, Egypt
Authors: Anwer E. , Rizk A. S. , Muaz A. , Abdelfadil M.
Published: October 2024

Waterflooding is a widely used and well-established secondary recovery technique that has been thoroughly studied over the last decades across the literature. However, the practical implementation of this technique in the field still raises many lessons to be learned. The objective of this paper is to present a detailed implementation framework that was developed for a waterflooding project in the western desert, Egypt. In addition, the paper emphasizes the major challenges faced during the implementation of the project and the proposed solutions. The considered reservoir is a sandstone characterized by moderate porosity/permeability values and underlain by a weak to moderate aquifer drive. The reservoir pressure and production rate declined severely from 2400 psi and 1000 BOPD to 600 psi and 400 BOPD, respectively, after production of only 260 MSTB. In addition, decline curve analysis (DCA) yielded a base case with very low recovery factor (10%). Accordingly, waterflooding project was implemented as a secondary recovery mechanism in order to support the reservoir pressure and improve the sweep efficiency. The original oil in place (OOIP) was evaluated using volumetric calculations and validated using rate-transient analysis (RTA)to be around 7 MMBO at the early production phase of the field and using material balance equation (MBE) later on. The results of the established framework yielded to the drilling of 12 new wells (8 producers and 4 injectors) to follow a combination of seven-spot and peripheral flood patterns, keeping into consideration an optimum voidage replacement ratio (VRR). This plan resulted in a significant enhancement of reservoir performance. Within just two months, the reservoir pressure increased by ±1000 psi, and production exceeded the pre-project rates by 4000 BOPD. Consequently, the expected recovery factor is anticipated to rise dramatically from 10% to 35% (incremental gain around 1.8 MMBO). For sandstone black oil reservoirs, following this framework will form a reference to evaluate any future waterflood projects. This reflects that integration between reservoir characterization and analytical engineering tools is powerful approach to achieve optimum field development plan which in turn reflects on the NPV of the project.
Optimizing ESP Power Consumption: A Case Study for Cost Reduction and Extended Runlife in Egypt
Authors: Salah Ahmed , Fayez Wael , Sabaa Ahmed , Mokhtar Mohamed , ElMenshawy A. D. , Diaa Ahmed
Published: October 2024

During times of volatile oil prices, optimization of production costs per barrel is a critical component for international upstream companies to ensure competitiveness and profitability. Therefore, the issue of maintaining oil production energy efficiency becomes more important nowadays. While Electrical Submersible Pumps (ESPs) are a reliable solution for lifting moderate to high fluid volumes from wells, a crucial challenge lies in maximizing system performance and minimizing daily energy consumption for each unit.

Agiba Petroleum Company relies on Electric Submersible Pumps (ESPs) for artificial lift in its onshore field (SWM-4) in Western Desert of Egypt. However, ESPs were operated by standalone generators and suffered from high diesel consumption. Additionally, several electrical failures encountered due to unstable input voltage and high motor temperature for low-rate wells. Those failures impacted both ESP run life and overall oil production efficiency. To address these limitations, this paper presents a case study exploring how replacing conventional ESPs with permanent magnet motors (PMMs) coupled with innovative power-saving pumps can significantly reduce power consumption and eliminate electrical failures.

A novel ESP system utilizing a Power Save high-efficiency ESP driven by a permanent magnet motor, has demonstrably improved run life in the SWM-4 fields. This configuration boasts a substantial increase in meantime between failures compared to traditional ESP systems. Additionally, a study revealed a substantial 30% reduction in total diesel consumption when compared to diesel consumption before the implementation. Additional benefits of PMMs include higher power factor, increased efficiency, synchronous operation, and higher power density. These advantages make it easier to address challenges like low productivity wells, unstable inflow, viscous fluids, and solids content. This case study outlines the artificial lift system selection process and the implementation of new PMM technology in ESP systems, covering conceptual aspects (design, specifications, and manufacturing), installation, and operational considerations (reliability and optimization).

In response to growing concerns about climate change, National Oil Companies (NOCs) are actively seeking ways to minimize greenhouse gas emissions from their operations. New advancements in ESP technology offer a promising solution: Power Save ESP systems driven by PMM. These systems not only improve profitability by lowering operating costs and reducing electricity requirements, but more importantly, they contribute significantly to environmental sustainability by decreasing overall power consumption throughout the ESP's lifespan.
Managed Surface Temperature/Pressure in Real-Time Drilling for Gas Migration and Wellbore Stability Detection in Subsurface
Authors: Wang Yarlong
Published: October 2024

Wellbore stability and gas migration detection from a gas-saturated formation are important for engineer during production and drilling. Erroneous onset of gas migration and wellbore collapse may be predicted if no accurate bottom hole pressure (BHP) is obtained in real time, despite a reliable geomechanics and gas migration models are utilized. Pressure along a tubing-annulus system must be calculated from the surface to the bottom hole, where thermal-hydraulic-mechanical (THM) may be coupled through wellbore wall to those inside the porous formations. A wellbore-reservoir model including tubing-annulus-reservoir system is established so that a pressure profile coupled to the inflow/outflow of the gas-saturated porous formations may be achievable. Coupled to each other inside the tubing-annulus system, thermal-hydraulic (TH) is managed and coupled to those THM in the formation so that wellbore stability and gas influx from the formation and migration along the annulus are forecasted. Along managed pressure drilling (MPD), managed temperature (MT) is also critically important both for BHP calculation so that the wellbore stability and blowout are accurately predicted. Temperature changes in the circulated fluid may affect the BHP calculation and stress concentration at wellbore wall. In an environment of narrow drilling mud window, MT may enlarge the window and reduce the active stress concentration at wellbore wall at the same time. Along a comprehensive reservoir-wellbore model, an engineering procedure with integrated logging-geomechanics model for inputs is proposed. In this procedure, WITSMAL data reading, MEM model buildup, and wellbore collapsing/blowout detection is incorporated. Real-time WITSMAL data is processed and transferred into MEM model so that real-time critical pressure may be predicted in formation ahead of the drilling bit. Both the MEM model and wellbore stability in the drilled section are examined and corrected if erroneous results are detected. A prediction ahead of the drilling bit is forecast and safe mud weight is recommended or adjusted if pre-design mud is not adequate. A novel logging-drilling procedure focusing on geomechanics is proposed. Reading real-time WITSMAL data and modifying MEM model, on which a real-time critical wellbore pressure may be verified, wellbore stability and migrated gas before blowout in drilled section may be identified. All these processes are critically helped by MT and such a real-time modification may allow an accurate forecasting on wellbore instability and blowout risk in the section ahead of drilling bit.
Calculating Indirect Emission for Business Support Activities by Using Emission Factor Improvement with Carbon Calculator Application
Authors: Ligafinza A. , Putra N. , Nurjanah S. , Kadarsih W. S. , _ Machfud , Natalie R. E.
Published: October 2024

As a company with a vision to become a global and sustainable energy company, we need to disclose several environmental aspects, one of which is emissions. Scope 1 & 2 emissions can easily be disclosed by the company as the data is within the company. However, for scope 3 emissions, particularly categories 6 & 7, which include business travel and employee commuting, calculation data resides with the employees. Therefore, a tool is needed to standardize the calculation methods for scope 3 categories 6 & 7 and also to accelerate data collection process. Hence, we have decided to develop an application called "Carbon Calculator."

The basic design of this application refers to the IPCC Guidelines for National Greenhouse Gas Inventories 2006. In general, greenhouse gas emissions (GHG) are calculated by multiplying activity data with emission factors. Activity data refers to energy consumption data according to the type used, while emission factors are coefficients indicating the amount of emissions per activity. In the technical implementation of emission calculations in the Carbon Calculator application, calculations will be adjusted based on data availability and emission factors. To simplify emission calculations from vehicles, the company processes advanced data on Net Calorific Value (NCV), emission factors, and fuel economy to obtain emission load calculation results from the use of private vehicles. Carbon calculator is a web-based application for GHG inventory that will be used by all workers.

PHE Carbon Calculator enhances emissions transparency for indirect emission (Scope 3 Category 6 & 7) and empowers PHE to proactively manage and reduce its environmental footprint and further indicates its commitment to global sustainability leadership. Currently, PHE is focused on familiarizing the use of the carbon calculator and conducting a campaign to disclose scope 3 emissions. At present, nearly all regions have participated in filling out the carbon calculator.

IPCC has provided the methodology for calculating GHG, however in this study we improve the emission factor specification to have more specific result in employee commuting and business travel disclosure. Future development of PHE Carbon Calculator will focus on scalability and integration of advanced analytics to further optimize sustainability initiatives.
Leveraging Weibull Analysis and Python Automation for Enhanced Failure Prediction of Electrical Submersible Pumps
Authors: Radwan O. , Salem Adel. M. , Ghareeb M. , Ibrahim F.
Published: October 2024

The primary objective of this study is to predict the failure of electrical submersible pumps (ESPs) by utilizing Weibull distribution analysis and Python coding, thereby enhancing the reliability and operational efficiency of ESPs in the petroleum industry. Moreover, it assists in intervention planning and rig count optimization.

This study employs a systematic approach involving the collection of ESP failure data, which is then analyzed using Weibull distribution to determine the shape and scale parameters. Python scripts are utilized to automate data processing, fitting the Weibull model, and conducting goodness-of-fit tests including the Anderson-Darling and Kolmogorov-Smirnov tests. This automation facilitates efficient data handling and analysis, ensuring accurate and reproducible results.

The analysis reveals that the Weibull distribution provides a good fit for the ESP failure data, as indicated by the p-values from the goodness-of-fit tests. The shape and scale parameters derived from the Weibull model enable the estimation of Mean Time to Failure (MTTF) and the probability of failure over specified time intervals. These insights are critical for maintenance planning and reliability improvement of ESPs. Furthermore, the automation process significantly reduces the time and effort required for data analysis, making it a practical tool for ongoing reliability assessments.

This paper introduces a novel integration of Weibull analysis with Python automation for ESP failure prediction, offering a significant improvement over traditional manual method. The approach enhances the reliability analysis process, providing valuable insights that contribute to the optimization of ESP maintenance strategies in the petroleum industry.
Water Injection Optimization for Natural Fractured Carbonate Reservoir: Descriptive Model Configuration Achieving Optimized Field Management: Khepri-D Field Case
Authors: Abdel Rahman M. Fathy , Elshaafie A. , Abdel-Fattah S. , Abdelazim A. , Fagelnour M. S.
Published: October 2024

Development of naturally fractured reservoirs, and water flooding pattern design for such reservoir is critical due to complicated nature of this type. The objective here, was how to maximize oil production and reserves through minimizing early breakthrough risk at the producers and define the optimal locations of new producers and injectors. In moderate development stages, the degree of confidence increased in static model including fracture network, permeability. facies and dynamic data (ex. production data) is relatively high.

A reservoir simulation study of the depletion drive oil mechanism in (Khepri-D field), was done to evaluate its original oil in place (OOIP), recovery factor (RF) and hence the optimum Field Development Plan (FDP) and injection pattern. Integration between reservoir, geological and petrophysical teams was organized to achieve this target. Reservoir study passed through different phases of history matching, along the reservoir lifetime. First history matching phase, was after one year of discovery and the second phase was after three years. In primary phase, the main concern was the pressure matching, which should be consistent with rate transient analysis and material balance rather than the water breakthrough. Consequently, building scenarios to describe static model, mainly includes representation of fracture network and geological structure of high productivity wells. Appropriate changes in structure model have been done to eliminate chance of early breakthrough. In the second phase, the main objective of the study was evaluation of proposed development injection and production wells. The preferred locations of wells would achieve maximum impact on the economics without losing reserves. The model uncertainties have been reduced by conducting several scenarios, especially on the structure model.

Finally, there were two scopes of results for the two phases of study. The first Phase, the study proved that current structure will not be representative and need to be reconfigured for achieving accurate history matching, in order to be consistent with reservoir management work, especially OOIP, that was estimated from reservoir analytical method. Drilling new wells was mandatory to confirm and capture additional reserves. as per the second phase of the study, dynamic modeling resulted in drilling a new well with initial oil production rate around 5000 STB/D. The proposal of new drilling opportunity, based on the structure configuration, facies, SCAL analysis, and fracture network achieving high ultimate recovery of about 40%.

This paper is a good example of how to develop depleted carbonate reservoirs achieving reasonable ultimate recovery through cooperative work between all disciplines and gathering data from different source to build integrated representative model.
Enhancing Rate of Penetration Predictions in the Surat Basin Using Supervised Machine Learning: A Comparative Study of ANN and XGBoost Models
Authors: Chang Mu , Zhong Ruizhi , Johnson Ray , Chen Zhongwei
Published: October 2024

The Surat Basin (the Basin) in Australia is rich in coal seam gas resources, characterized by up to 2500 meters of relatively continuous sediment deposition. However, the Basin presents significant geological challenges, including extended drilling cycles and rising costs, necessitating precise rate-of-penetration (ROP) predictions. Current models often rely on engineers' experience and exhibit considerable errors (typically between 25%-50%) and unstable performance. This highlights the need for refined approaches to improve ROP prediction accuracy. This study employs supervised machine learning methods, specifically Artificial Neural Networks (ANN) and Extreme Gradient Boosting (XGBoost), to predict ROP. Data were collected and preprocessed from five wells in the Surat Basin, divided into three training/validation wells and two testing wells. The data underwent detailed cleaning and processing, including selecting long drilling periods and eliminating low rotations per minute (RPM) points during frequent drilling pipe extensions. For model training, hyperparameter tuning and cross-validation were employed to optimize the models. Evaluation metrics included Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and the Coefficient of Determination (R²).

Both XGBoost and ANN models delivered good results, with XGBoost generally outperforming ANN, particularly after data filtering. The two testing wells (i.e., W2 and W6) showed enhanced performance through data filtering, which removed noise and irrelevant data points. For well W2, the results were R² of 0.59, MAE of 10.2 m/h, RMSE of 13.5 m/h, and MAPE of 14.3%. For well W6, the results were R² of 0.55, MAE of 11.7 m/h, RMSE of 15.5 m/h, and MAPE of 15.8%. The predicted ROP curves closely matched the actual drilling ROP curves. The application of ANN and XGBoost for ROP prediction demonstrates significant improvements in accuracy and predictability, with XGBoost showing superior performance. This study provides a robust and reliable tool for optimizing drilling operations in complex geological settings, contributing to more efficient coal seam gas extraction.
Comprehensive Integrated Study on a Novel Completion Technology of Hybrid ESP-Gas Lift System for a Gas Lift Field in the GOS
Authors: Magdy K. M. , Moussa A. , Helmy A. G. , Abd Elrahman M. , Aly Seida A. , Khattab A. , Sobhy M. , Ibrahim M. , Hammam M. , Elbanna B. , Korish M. , El-Sheikh M. I.
Published: October 2024

GS327 field is a small field located in the central of GOS with a relative heavier oil than the other neighboring fields which affects the sweeping efficiency. Started production in 1986 with a peak production in 2007. The field is being operated under gas lift artificial method, producing mainly from two reservoirs with high petro-physical parameters and very good sand quality in addition to be supported by a strong aquifer. One of our main responsibilities as petroleum engineers is to select the optimum artificial lift technology to maximize the field production. In an especially limited offshore field, not all methods are applicable due to the platform spaces, operating costs, and system reliability.

Concern for alternative lifting methods has arisen since 2012, due to the limitation of gas lift injection capacity that is no longer adequate for the current and future development wells at that time. Moreover, the network system is suffering from bottleneck causing back pressure and losing more oil, this is mainly due to the gas effect in the production lines. After due consideration, the Electrical Submersible Pump (ESP) was finally decided as the key driver to reinforce well production performance. Moreover, the gas lift has been brought in as a backup in case of pump failure, which is not only to prolong well life, save workover expenditure but also boost production if operating in hybrid mode.

A comprehensive integrated study was carried on to evaluate the switching from Gas Lift operated field to the novel hybrid ESP Gas Lift system taking the advantage of the ESP wide range of outflow performance to increase the oil production and hence adding more reserve. Initializing the study first by using the reservoir analytical approaches to assess the added value of the ESP; WOR Exercise, analog performance, asset integrated modeling by GAP MBAL PROSPER was created which revealed we can add around 1.5 MMSTBO as an incremental reserve. Realizing the construction, layout and electricity power sources were critical points that took much effort to assess. In addition the risk of sand production due to the higher drawdown from the ESP was studied as well from the geomechanics team to mitigate it.Finally a complete reservoir simulation model was created to integrate all the inputs, assumptions, risks and uncertainties which revealed we have a very good room to increase the sweeping efficiency, drawing out more oil and increase the reserve.

In this paper, we present sequential events from the conceptual study to the designed pilot test. It is a very good example of managing uncertainty by integrating different data to convert it into reality that can be translated ultimately into oil production and revenues
Innovative Machine Learning Approach to Locate the Remaining Gas
Authors: Mohamed Islam A. , Hosny Ahmed , Amin Sameh
Published: October 2024

Locating remaining gas in a producing gas field poses several challenges, primarily due to complexities in reservoir dynamics, data availability, and technological limitations. Gas reservoirs often exhibit complex geological formations and heterogeneities. Variations in porosity, permeability, and rock types can create irregular gas distribution, making it difficult to accurately predict where remaining gas pockets might be located. Moreover, sparse well coverage, incomplete data sets, or inaccuracies in historical data can hinder accurate reservoir modeling and forecasting. Addressing these challenges requires a multidisciplinary approach combining geological understanding, advanced reservoir engineering, and innovative technologies. We designed a new approach that predicts the reservoir properties via Machine Learning algorithm, Neural Network Inversion, in order to locate the remaining reserves. In this workflow, we predict 3D volumes of porosity and water saturation using deep learning neural network algorithm. Then, we resampled these volumes into reservoir 3D structural grid. Then, we defined the net and calculated the gas in-place for different reservoir segments. And finally compare these calculations with the dynamic production data. The proposed workflow was calibrated through multiple blind well tests and the predictions showed high accuracy. The results of the project were astonishing. 500+ billion cubic feet of gas were added to the portfolio in the form of infill and near-field exploration opportunities. Consequently, a next phase of development was proposed based on the findings. The proposed approach demonstrates that the data integration and advanced predictive modeling are key strategies to optimize gas recovery and extend the productive life of gas fields.