bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Laboratory Approach to Offshore Analysis: No Compromise on Fluid Composition
Authors: Pearson S. , Winkworth N. H , Langford M. W.
Published: November 2024

Presented here is the development of a new approach to compositional analysis, allowing data to be generated in offshore and field environments with the same level of quality as established laboratory measurements.

Availability of reliable fluid composition traditionally relies on established, often remote, laboratories, resulting in considerable delays before data is available for reservoir models and other field evaluations. Previous attempts to generate compositional data onsite have compromised quality in order to improve portability and reduce reporting time.

The innovative approach presented is a result of technology assessment, method refinement and extensive testing including comparison with traditional laboratory techniques. Evaluation of deviations in compositional measurements between the techniques was performed, with the analytical uncertainties of the methods considered.

Testing commenced using certified reference materials from a variety of sources and extended to include analysis of real samples available in the lab facility.

Comparison with laboratory techniques showed excellent compositional agreement, well within the expected uncertainties and acceptable tolerances of the methods, and the certified materials.

Improvements in column selection and method optimization allowed the reduction of run times to circa 30 minutes, enabling completion of blank, verification and sample runs within the timespan of a single shift and reporting of fully reviewed data within 8 hours of sample collection or completion of sample restoration.

Samples are run in triplicate, with QC checks that mirror those performed in the laboratory to generate confidence in the offshore data.

This novel approach allows laboratory quality compositional data to be generated in the field without compromising on the calibration, verification and QC processes which give confidence in the measurements.

Earlier availability of this data enables quicker decision-making without compromising on the quality of the measurements.
Improving the Efficiency of Active and Passive DAS Seismic Monitoring in an Onshore CCUS Demonstration Field
Authors: Watanabe Y. , Mouri T. , Nakayama S.
Published: November 2024

Long-term monitoring of injected CO2 in Carbon Capture Utilization and Storage (CCUS) projects, particularly seismic monitoring, constitutes a substantial portion of operational costs, despite CCUS's critical role in achieving carbon neutrality. Distributed Acoustic Sensing (DAS) technology offers a solution to reduce the cost and workload associated with monitoring in CCUS projects. This study focuses on improving operational efficiency by reviewing techniques for active seismic acquisition and continuous passive seismic monitoring, as demonstrated by Nakayama et al. (2024a, 2024b, and 2024c) in an onshore CCUS field test at the Minami-Aga field, a depleted oilfield in Japan. For active seismic monitoring, a walk-away DAS vertical seismic profiling (DAS-VSP) survey using a simultaneous source acquisition method, known as the slip-sweep method, was conducted as a baseline seismic survey. The comparison between traditional and slip-sweep acquisition methods revealed no significant differences in data quality, with the slip-sweep method nearly doubling acquisition efficiency. To manage the vast amounts of data generated during continuous passive seismic monitoring, a DAS system and real time data handling framework were employed. Microseismic (MS) events during the CO2 injection test were detected and located using a real time data analysis approach, resulting in the identification of approximately 1,200 events with estimations of their locations and moment magnitudes. The DAS system demonstrated high sensitivity to small-magnitude events. These field trials underscore the importance of enhancing operational efficiency to fully realize the potential of DAS in both active and passive seismic monitoring within CCUS projects.
Successful Reactivation of Offshore Dead Oil Well with the Gas Produced by High Gas Cut Adjacent Well Using a Rig-Less Retrofit Gas Lift System - First Worldwide
Authors: Shokry A. , Biyanni H. , Abdulla M. , Dwivedi V. , Yakovlev T. , El-Sayed M. A. , Najy A. , Agrawal P. , Keshtta O. , Sulaiman A. , ElSheikh H. , Sabri A. , Alhammadi N. , Al-Hassani S. D.
Published: November 2024

Globally, in-active oil-producing strings constitute a substantial portion of the active ones, posing a considerable challenge for NOCs and operators. Monitoring the KPIs of these inactive strings is essential not only to prevent deferred production but also to evaluate operational efficiency and environmental impacts, such as carbon footprints.

For a national oil company in UAE, the objective to reduce the number of in-active string from an offshore oilfield became a catalyst for innovative thinking, leading to the successful revival of a dead oil well.

The well in focus was a natural oil producer (without any provisions of gas lift) that had become in-active due to liquid loading. While the retrofit gas lifting was the preferred solution, there was no availability of lift gas or gas injection network to support the revival plan. A nearby well with very high gas production (HGOR) was identified as the "donor" well to provide the lift gas, resulting in a novel retrofit gas lifting solution.

The paper will describe an innovative approach to rejuvenate the "receiver" well by utilizing the produced hydrocarbons (as lift gas) from the "donor" well in a rig-less intervention environment. The paper aims to present a comprehensive overview of the entire process, from the initial conceptual design and simulation studies to the selection of a retrofit gas lift system (specifically, a straddle packer- based system), as well as the subsequent operation planning and field installation.

The innovative revival approach led to the successful reactivation of the well, resulting in significant production gains, which were confirmed through well testing. This paper will also emphasize the benefits of this approach, including quantifiable cost savings (with minimal CAPEX) and reduced carbon footprints. Additionally, the installation of a retrofit gas lift system can be completed in the short term without the need for an expensive rig workover.

The paper will demonstrate the advantages of the "life of field" gas lift design approach that was implemented for the "receiver" well. This approach involved determining the optimal set points for gas lift depth, injection rate, orifice size, and other parameters to accommodate the varying field conditions for both the "receiver" and "donor" wells.

The "receiver"/"donor" arrangement between the wells was carefully analyzed in accordance with established well integrity guidelines and industry best safety practices. This analysis was used to develop operational procedures and steps that were crucial to the success of the operation and served as a testament to the effectiveness of teamwork with aligned objectives.
Integrating Seismic and Well Data for Cementation Limit Determination: A Case Study in the Upper Arab D Reservoir, Sour Gas Field in the SW of Abu Dhabi, United Arab Emirates
Authors: Isdiawan Agusandi , Al Darmaki Fatima , O'callaghan Earl John , Al Teneiji Moza , Corrales Alvaro
Published: November 2024

The objective of this paper is to demonstrate the advantages of integrating seismic and well data in the Upper Arab D Reservoir for defining the cementation limit (CML) and improving the reliability of field and reservoir dimension for Gas in Place estimation by employing a scientific method that includes data interpretation, attribute analysis, and reservoir characterization to minimize uncertainties. The results demonstrate the value of this methodology, providing a fuller understanding of reservoir heterogeneity (porous and cemented rocks) and enabling reduced GIP estimation uncertainty. This approach contributes significantly to reservoir management strategies, aiding in reservoir modeling and development planning in the complex reservoirs of the Upper Arab D. The process of continuously updating the CML grid and integrating it into the reservoir model progresses geological understanding and improves operational decision making for future development wells.
Enhancing Pipeline Integrity Data Management through Power BI and PI Dashboard Approach
Authors: Bulushi K. Al , Mawali F. Al , Alrashdi I.
Published: November 2024

With ageing facilities, maintaining integrity of the pipeline via proactive maintenance becomes vital to reduce the operation risk level and zero harm to surroundings. Data-centered approach allows stakeholders to prioritize critical assets, allocate resources efficiently, and ensures proactive measures to maintain the integrity. The novel approach present success story of integrating massive data that affects the pipeline integrity by providing visionary analysis of all findings from different used inspection techniques, as a result it prioritizes inspection and repair program with minimizing downtime and disruptions due to unpredicted damage and defect, through utilizing available digital resources.

This paper presents an innovative approach to of data management and interpretation in the oil and gas industry: ensuring integrity, safe, and reliable operation of the critical pipelines as part of Oxy management system. The focus lies on introducing advanced data analytics through the implementation of a Microsoft Power BI visualization and OSI PI dashboards. This by integrating real-time Integrity Operating Windows (IOW) WITH inspection reports to address potential damage mode affecting segment of a pipeline. The tool accelerates maintenance program via data-driven decision making, by proactive identification of potential issues and leak points that affect the environment to ensure not leaving any barrel behind. The tool starts by examining the latest two In Line Inspection (ILI) reports via aligning common features such as joint number and distance of defect from the weld to illustrates differences in wall thickness and pitting depth of reported anomalies in the pipeline. Then, the data integrated with pipeline layout (topography) and other Cathodic Protection (CP) surveys, such as ON Off survey, Direct Current Voltage Gradient (DCVG) and Close-Interval Potential Survey (CIPS), so that condition and defects aligned with pipeline chainage. On the other side, the tool also gathers data for corrosion inhibitor treatment program performance, readings of bacteria, corrosion coupons, basic sediment, and water (%BS&W) and integrity operating windows (IOW). The dataset correlated to create Power BI and PI dashboards that effectively communicates operational and statistical data points through informative graphs and simplified tables, providing deep overview of the pipeline's operational condition and up-to date results from related datasets.
Successful Deployment of Ultra Smartwell Enable Maximum Reservoir Contact for Enhanced Production Recovery
Authors: Juvarajah Navindran , Mirza Omar T. , Nasser Reem , Saqib Talha , Keshtta Osama M. , Al Hajri Saaed Salem , Sabri Abdel Moez M. , Alhammadi Yousef A.
Published: November 2024

The focus of this paper is the effective implementation of an "ULTRA SMARTWELL", a smart completion system integrated with advanced remote sensing and monitoring technology, employed across a substantial long horizontal drain section. It encompasses the utilization of the longest intelligent completion design ever utilized in the UAE, extending 18,800 feet, from an offshore jack-up rig situated in Offshore Abu Dhabi, UAE. This approach optimized on achieving maximum reservoir contact, leading to enhanced production recovery

During the concept selection phase, a thorough engineering feasibility study was conducted. Traditional intelligent completions typically require drilling and completing various horizontal drains, increasing operational risks and costs. The innovative "ULTRA SMARTWELL" design calls for a single 8-1/2 in horizontal well and a non-cemented 7in liner with swell packers for zonal isolation and segmentation. This approach includes remote sensing and live monitoring to manage any water or gas breakthrough, greatly enhancing oil recovery. It also boasts a design that minimizes the need for interventions because surface-controlled downhole valves and gauges allow for remote well performance monitoring.

The paper will examine various procedures and difficulties encountered while implementing the completion string in the lengthy horizontal segment, following post-completion intervention. This innovative deployment method also achieved considerable capital expenditure savings by cutting approx.16 days from rig operations. Additionally, a notable increase in value was achieved with enhanced hydrocarbon recovery totaling up to ~4.67 million stock tank barrels (MMSTB), attributable to remote sensing and the capacity to manage high gas/oil ratios and water/gas entry, thereby prolonging the productive life of the well.
How Mechanical Principles Affect Production from Deep and Complex Gas Reservoirs
Authors: Hamid Osman , Abdalrahman Eslam M.
Published: November 2024

This study aims to elucidate the mechanical principles governing gas production from deep and complex reservoirs. Focusing on geomechanics, contact mechanics, fluid flow and deformation, poromechanics, and damage mechanics, the research seeks to determine their collective impact on the efficiency and safety of gas extraction.

Employing the numerical modeling approaches, the study investigates subsurface stress conditions, grain-to-grain interactions, fluid-rock interplay, and fracture development. A coupled fluid-solid interaction model is developed to simulate pressure distribution and strain on the rock matrix. The methodology integrates advanced constitutive models to address the non-linear and time-dependent behaviors of reservoir rocks under stress.

The research identifies key factors influencing reservoir performance, including stress-induced permeability and porosity changes and fracture and fault reactivation. Simulations reveal that optimal gas production is contingent on maintaining structural integrity, which is influenced by effective stress adjustments and material damage thresholds.

The study's novelty lies in its integrated numerical modeling approach, which synthesizes various mechanical principles within a singular predictive model. This model advances the current understanding of deep reservoir behavior by incorporating non-linear rock mechanics and real-time reservoir conditions.

Concluding that a multidisciplinary mechanical approach is vital for sustainable gas extraction, the study provides a strategic framework for production optimization in deep and complex reservoirs. The resulting tool offers significant improvements in predicting and managing the challenges of gas production, fostering enhanced recovery and minimization of environmental risks.
Holistic Approach to Tackle Proppant Flowback & Coal Fines Challenges through In-House Engineered Chemical Formulation
Authors: Nain Pooja , Qamruzzaman Mohammed , Mhaske Ganesh , Nischal Rajiv
Published: November 2024

ABSTRACT

This paper addresses the challenges associated with coal bed methane (CBM) well dewatering, particularly the issue of proppant flowback and production of coal fines. The primary objective is to mitigate the impairment in fracture permeability caused by fines migration and assess the suitability of a developed Proppant and Fines Agglomerating Formulation (PFAF).

The devised PFAF system coats proppant surfaces thus enhancing agglomeration & preventing flowback. It was synthesized after extensive evaluation of various chemicals. Agglomeration Tests, Microscopic imaging and SEM imaging was conducted to select the best performing PFAF formulation. Optimal concentration was determined through measuring maximum proppant free production rate from proppant pack. Effect of PFAF on permeability was evaluated on fracture conductivity setup. A visualization assembly was fabricated to visualize the migration of fines in proppant pack before and after treatment with PFAF. Compatibility of PFAF with conventional fracturing fluid was evaluated through rheological tests to employ PFAF during Fracturing.

Extensive laboratory studies indicate that the developed PFAF, a reaction product of an amine and ester exhibits promising results thereby reducing clean-up time and cost. The proppant treated with PFAF agglomerated and descended slowly as one piece of consolidated mass indicating reduced proppant flowback, as compared to untreated proppant which fell as individual sand grains. Microscopic study shows uniform adsorption and SEM imaging indicates non-glue like behaviour with developed formulation. The Maximum Proppant Free Production rate significantly increased post-treatment, from 350 cc/min to 900 cc/min, indicating proppant consolidation. No significant change was observed in the permeability of the treated proppant pack. Fines Migration visualization shows the retention of coal fines in the treated pack, affirming the efficacy of PFAF in mitigating coal fines. No adverse behavior was observed in compatibility study of PFAF with conventional guar based fracturing fluid. Near Zero magnitude zeta potential values were obtained with PFAF which corroborated with other test results.

This paper introduces a novel Proppant and Fines Agglomerating Formulation (PFAF) to address fines-related challenges in CBM wells. PFAF demonstrates unique consolidation properties without compromising the fracture conductivity, as demonstrated by laboratory studies. The paper contributes additive information to the existing literature by presenting a practical solution for mitigating fines migration and proppant flowback in CBM wells.
Improved Fault Definition and Seismic Images Through Full Azimuth Angle Domain Imaging in A Dense Single Receiver Broadband Acquired Datasets within a Low Dune Area
Authors: Vargas Jose Edgardo , Utami Y. P. , Ofowena F. O. , Ahmed J.
Published: November 2024

Full azimuth angle domain imaging (CRAM-LAD) was applied on a +1000 km2 single-source, single-receiver full azimuth seismic survey targeting a better fault definition, fracture characterization and reservoir management of very subtle low-relief structures, geological environments of carbonate reservoirs in the Middle East desert environment. The previous seismic processing in this area was based on conventional pre-stack time and depth Kirchhoff migrations methods. New results allow us to have a better characterization of faults and fractures. Using EarthStudy 360 full-azimuth anisotropic seismic imaging in Local Angle Domain (LAD) technology, we were able to better delimitate structural inhomogeneities in the target reservoir levels, including small fault detection and characterization. The use of angle gathers allows us to improve the shallow velocities leading to better statics models incorporated in the Depth Velocity Model along with a multi-azimuth tomography also in the angle domain to improve the velocities in the overburden. Post-migration (imaging) procedures separate reflections from diffraction on directional angle gathers. Post-stack seismic attributes using diffracted events can show geological features that normal imaging methods cannot. Main achievements include the production of Full Azimuth, angle-dependent reflection and directional (dip and azimuth) data components. From Reflection angle gathers with higher signal to noise ratio, we obtained seismic section for a reliable geological interpretation preferred by interpreters and angle stacks with much less stretching effects in comparison with Kirchhoff methods more suitable for seismic Inversion. AVA amplitudes and attributes are superior in comparison to those obtained in previous studies. The deepest reservoir exhibits a better continuity for reservoir still on development. Directional gathers allow us to split its specular component from which we generated a seismic volume with higher signal to noise ratio in the reservoir levels. The diffracted energy also extracted using designed filter in this project, allows to extract geological features like small faults and fractures that traditional imaging methods are not able to map accurately. The rich azimuth information and angle ready datasets, obtained from non-regularized pre-migrated gathers, clearly define faulty planes, channels and karst zones from top to bottom. CRAM LAD imaging is widely used in the middle east for more effective imaging and analysis in fracture carbonate reservoirs. Here we demonstrate that can be used to improve the image quality for desert environments, especially in full azimuth single receiver datasets. AVAZ inversion for the definition of small fractures based in horizontal anisotropy measurements is also a benefit of the application of this kind of imaging technology.
Enhancing the Efficiency of Refining Processes: A Desktop Solution for Predicting FCC Yield Profiles
Authors: Maity Pintu , Khande Ajay , Majumder Supriyo , Dasila Prabha , Thota Chiranjeevi
Published: November 2024

The current state of FCC technology has the potential to dictate the overall profitability of any complex oil refinery worldwide, where the catalyst plays a central role in maximizing fuel and olefin yields. Innovations in FCC catalysis have led to higher conversion rates, improved selectivity, and better tolerance to contaminants. Consequently, every FCC catalyst changeover presents an opportunity to enhance the refinery’s profit margin. However, this potential increment in margin necessitates thorough testing and selection of candidate optimum catalysts which is often a time-consuming process. While various computational models based on first principles, databases, linear programming, or artificial intelligence exist to expedite this process, they typically serve as intermediaries between laboratory experiments and commercial yield predictions.

To streamline this process, the R&D team at Bharat Petroleum Corporation Limited (BPCL) has developed a proprietary Yield Prediction (Y-P) model. This model is designed to eliminate the need for experimental catalyst testing by estimating potential yield, selectivity, and conversion based on FCC feed and catalyst characteristics. The Y-P model employs a mathematical kinetic model using the tenlump scheme, integrating feed and catalyst properties into the prediction algorithm. By leveraging multivariate regression, lumped reaction mechanisms, and artificial neural networks, the model utilizes feedstock properties such as con-carbon, density, distillation, sulfur/nitrogen content, and catalyst properties like surface area, unit cell size, and acidity to predict commercial plant yields.

The trial results of the Y-P model have shown strong alignment with conventional in-house catalyst evaluation methods, demonstrating its reliability and accuracy. This model not only facilitates the selection of FCC catalysts but also enables their reformulation to meet changing market demands. By bringing catalyst selection to the operator’s fingertips, the Y-P model significantly enhances the efficiency and profitability of refinery operations.
Digital Twins Revolutionizing Oil and Gas Industry Optimizing Drilling Operations with Physics Informed AI
Authors: Gandikota R. A. , Chennoufi N. , Hadad T.
Published: November 2024

Digital technologies have disrupted every industry in recent years, and the oil and gas industry are no exception. One of the most significant advancements is the utilization of digital rig technologies, which have revolutionized drilling processes, monitoring, and well management. By implementing physics-informed-AI based real-time Digital Twins operating at the edge, companies can maximize performance, efficiency, and cost reduction.

In this study a digital twin with physics informed AI is presented. An efficient physics-based time domain model coupled with Machine Learning algorithms, forms the core of this innovative approach. The method utilizes performance data from small set of offset wells to continually optimize and update operating conditions. Its objective is twofold: minimizing predicted shock and vibrations and reducing mechanical specific energy while maximizing drilling rates.

The real-time edge implementation has demonstrated significant improvements from well to well, including enhanced weight transfer to the bit, consistent top drive RPM performance, and reduced shock and vibrations. As a result, average drilling performance has improved by 40%, translating to expedited drilling operations and decreased overall drilling costs.
Evaluation of a Novel Emulsion Preparation Method for Reducing Water-Cut in Production
Authors: Othman A. , Aljawad M. S. , Al-Ramadan M. , Kamal M. S. , Al-Taq A. A. , Al-Mohsin A.
Published: November 2024

High water cut associated with oil wells can shorten their production life. Globally, water accounted for the majority of the total output from wells. This excess water must be disposed of or treated to a specific standard, depending on the treatment objectives. The industry has developed numerous techniques to decrease the water produced alongside oil production. This study introduces a novel method to pump polymer and crosslinker emulsified system to block water production.

The system is designed to gel upon contact with water but form an emulsion in the presence of crude oil. The research was conducted in multiple stages. The objective is to create a water-in-oil emulsion using an emulsifier, introduce the same emulsifier to the crude oil, and then inject the polymer and the crosslinker. The viscosity of the polymer, polymer with crude, polymer with water, crude with emulsifier, and water with emulsifier were recorded. One emulsifier was selected from three emulsifiers when tested with crude oil and water separately the better type was U-108 emulsifier. Then the diluted polymer and the crosslinker were added and the viscosity was measured. The concentrations used in the study and added in the same order are; 53-60 vol. % of water or crude oil, 5 vol. % emulsifier, 2.5 wt. % pH buffer powder, 30-35 vol.% polymer or copolymer, and 4 vol. % crosslinker. These systems were mixed at two different mixing rates to mimic the pumping condition.

The initial evaluation of the diluted polymer viscosity at the standard condition and 100 s-1 had a viscosity of 12 cP. The emulsifier raised the viscosity of the linear systems in both oil and water samples, the emulsified linear water has a viscosity of 231 cP at room temperature, compared to 253 cP for crude oil. After 20 hrs at 94 C temperature, the viscosity was 1600 cp for the crosslinked water system and 3300 cp for the emulsified crosslinked water system, the emulsifier raised the viscosity value triple as the non-emulsified system. However, at the same conditions both the crosslinked and emulsified crosslinked crude oil had viscosities less than 20 cp. This preparation method can be applied to the field as a novel pumping method; the pumped emulsifier is proposed to make emulsion when it goes into the oil zone, while no emulsion is formed in the water zone. The formation of the emulsion in the oil zone will prevent crosslinking mechanisms. This emulsion is followed by water which raises the viscosity in the oil zone and not in the water zone which helps in viscous fluid diversion. When the polymer-crosslinker system reaches the water zone the gel is formed as no emulsion formed in the formation. A core flooding experiment was used to prove the two ideas shown in this paper.

Two concepts to show in the paper are a) the same fluid pumped into the formation and gelates in the water zone but not in the oil zone, and b) the diverting mechanism based on the viscosity value.
Utilization of Low-Grade Waste Heat by Capitalizing ORC to Maximize Hydrocarbon Yield and Reduce CO2 Emissions in Upstream Crude Processing
Authors: Amminudin K A. , Kamandahalli S.
Published: November 2024

Efficiency enhancements and energy conservation in existing operational facilities have become increasingly essential undertakings in the pursuit of optimization and decarbonization. This paper aims to shed light on how to use low-grade waste heat to improve the process, increase stable condensate production, reduce power consumption, and reduce the CO2 footprint in the gas processing train of a crude oil production facility using the Organic Rankine Cycle (ORC) system.

In the Gas Oil Separation Plant (GOSP), the gases separated from high-pressure production traps and low-pressure production traps are compressed and cooled by fin-fan coolers. The compressor's discharge heat serves as a low-grade waste heat source. The proposed approach is to utilize this low-grade waste heat for the benefit of process improvement by employing the Organic Rankine Cycle (ORC) system instead of releasing this waste heat into the ambient through air-cooled fin-fan coolers. Currently, the compressor discharge gases are cooled down to 145°F by using air coolers; however, with the ORC, the compressor discharge gases will be cooled down to the process requirement of 80 to 90°F

The cooling of the compressor discharge gas to 80 to 90°F by using the ORC system will help in condensing the heavier hydrocarbons upfront, resulting in an increase in condensate production, removing the moisture from the gas by condensing before entering into TEG system and reducing the volume of the gases to be processed in the subsequent steps. The lower gas temperature for the LP and HP compressor suction will result in less heat from compression, hence lowering the power requirement of the compressors. Practically, we can eliminate after cooler operation on a compressor train and generate additional power from ORC. The refrigeration system's condensing load will also be reduced due to low temperatures. The power generated by ORC will be connected to a local electrical grid to operate auxiliary equipment, which will offset some of the energy power imported from the grid.

This study provides an extensive overview of gas train systems and how the ORC system can be effectively used. Traditionally, the ORC system has been utilized merely to generate power; however, this study focuses on the technological benefits of improving the process, optimizing power utilization, increasing production, and minimizing CO2 emissions in an operating facility. This study aims to illustrate the advantages and potential improvements that can be achieved by applying the ORC system. The opportunities for implementing the technology are enormous, as it has the potential to deliver annual value creations in increased product recovery and electricity savings.
Predicting HPAM Polymer Yield Viscosity using Neural Networks
Authors: Maillon Rémi , Dupuis Guillaume
Published: November 2024

This work follows paper SPE- 216592-MS presented in October 2023 and gives an update of the machine learning model developed by SNF to predict HPAM polymer yield viscosity under various conditions. Major improvements to the model are as follows:

The random forest algorithm has been replaced by a neural network to predict EOR polymer yield viscosity. The rheological dataset has been extended to include more than 95,000 lab measurements compared to 69,000 previously. The rheological dataset has been filtered using the DBSCAN clustering algorithm to detect anomalies in the polymer flow curves and 1,030 erroneous lab measurements could be removed from the training dataset. A more limited selection of input features has been used for the prediction with only 7 variables compared to 8 previously. Only the polymer ATBS content was retained and deemed sufficient to characterize the polymer chemistry due to strong correlations between acrylamide and ATBS contents. A new web interface was developed to deploy the model to the end user.

These modifications helped improving the model's prediction accuracy while limiting the overfitting tendency. The mean absolute percentage error for the yield viscosity prediction dropped from 35.8 % down to 16.0%.

A second objective of the machine learning model was to assist lab technicians with polymer screening. The model was hence adapted to select suitable polymers based on the target viscosity and reservoir conditions (reservoir permeability, temperature, brine salinity and hardness) while ranking those selected polymers to minimize the required polymer concentration and cost.

In addition to those efforts, another app was developed to visualize the different polymer flow curves present in the rheological dataset while comparing them with fitted regression lines based on the Carreau – Yasuda equation. Parameters such as relaxation time λ or power law index n have been derived by fitting the Carreau – Yasuda model on 4,680 polymer flow curves.
Predicting System Surface Parameters Using Artificial Neural Network
Authors: Eltrissi Mohammad , Yousef Omar
Published: November 2024

The prediction of apparent surface torque and the system standpipe pressure holds immense importance in any automated system or digital twin solution. These parameters provide crucial insights that are instrumental in determining various factors in the digitalized drilling application workspace. However, obtaining these values prior to the operation poses a challenge due to their dependence on numerous lithological and operational parameters. Due to the problem of non-linearity, a statistical tool is favored in developing a prediction system for these features. Artificial neural networks (ANN), a statistical tool in machine learning (ML), can effectively predict the system standpipe pressure and the apparent surface torque.

A logical base data cleaning process is conducted to ensure consciousness cleaning of the dataset based on statistical feature exploration, feature engineering, and domain knowledge. A large dataset of 336 wells from a single operator across four concessions is used to train the ANN. This large dataset overcomes the problem of overfitting within the designed ANN, while extended training epochs avoid the underfitting problem. An extensive trial and error alternatives selection process was used to select the ANN optimum topography. The Nesterov-accelerated adaptive moment estimation algorithm is the optimization algorithm used to improve the ANN solution's training efficiency and convergence speed.

The developed ANN achieved 93.09% and 92.62% accuracy for the apparent surface torque and the standpipe pressure feature, respectively, in the non-biased testing of the result. The work investigating the low-order topography for the ANN shows poor accuracy against the high and more sophisticated topography of the ANN. One of the ANN's behaviors realized is that enhancing the prediction accuracy for one feature results in a deterioration in the prediction accuracy of the other.

Several attempts were made to create an automated drilling system; however, these attempts focused on the larger picture of the model and ignored the vital components that the calculated and predicted calculations are based on. System standpipe pressure and apparent surface torque prediction provide a solid foundation for an integrated system. The system's development used non-stochastic gradient decent tools to achieve the global minimum of the solution, contrary to most developed models' approaches to that topic. The high prediction accuracy of the developed ANN using the large dataset for training is a differentiator for this model.
Laser Descaling Robot for Long Range Scale Removal Applications
Authors: Abdelmoula Hichem , Jabari Rami , Batarseh Sameeh , Alerigi Damian San Roman
Published: November 2024

Scale deposits gradually accumulate within flowlines, often resulting in obstructions. At present, the descaling process primarily relies on chemical cleaning, pigging, or hydroblasting methods. However, these approaches are range limited, requires complex step-up, and carry the risk of potential damage to the inner pipe surface. To overcome these issues, we developed a laser descaling robot that can move within the flowline while carrying a high-power laser that can remove materials in the scale buildup.

The designed robot for descaling operations utilizes an in-pipe crawler designed to be centralized in the pipe. The laser collimator is affixed to a mount and positioned near the edge of the pipe. The robot's mount is attached to the end of the crawler and is equipped with a motor that facilitates the rotation of the collimator. Additionally, the robot is equipped with various hoses and accessories necessary for laser descaling activities. Furthermore, for real-time monitoring of the descaling process, a camera is affixed to the laser mount, ensuring that the operation can be closely observed as it unfolds.

A test setup is constructed extending over 60 m with varying pipes' internal diameters. Some of these pipes have a 7.65-inch internal diameter, while others have an 8-inch internal diameter. Additionally, the pipe setup features a 10 m radius curvature to verify the descaling robot's capability to navigate curved paths. Furthermore, aside from the tether, the robot is connected to multiple hoses that replicate the presence of nitrogen and vacuum tubes, which are essential components in real descaling operations. The robot was able to traverse the entire length of the pipe without encountering any issues. The camera output was recorded as the pipe traversal job was unfolding. The robot demonstrated smooth adaptation to varying pipe internal diameters. The articulated mount efficiently rotated during motion without causing any entanglement of the cables and hoses. Moreover, the robot was successfully retrieved without causing damage to any of the cables or hoses, highlighting its precision and safety during the operation.

The current design successfully validates the concept of remote laser descaling, showcasing the robot's capacity to carry the laser and all the required auxiliary hoses through long pipes. This novel method will allow the replacement of existing descaling methods while allowing a safer, more controlled, and long-range scale removal procedure.
Harnessing the Power of AI: a Data-Driven Well Reservoir Virtual Flow Metering Tool Accessible to All
Authors: Papot F. , Maurin P. , Dabat F. , Solans P. , Cyrot M. , Al-Sahely A.
Published: November 2024

Data-driven Virtual Flow Metering (VFM) by Machine Learning is an increasingly attractive method to perform multiphase flow metering in Oil and Gas production systems. A VFM is a complement to physical meters, using the continuous available field measurements such as tubing pressures, temperatures, and other relevant parameters (choke opening, activation parameters, etc.) as inputs to provide flow rate estimates at any given point of the production and injection network. Good knowledge of Flow Metering is required for production optimization, flow assurance, reservoir management and allocation activities.

In the allocation context, production and injection figures are typically computed monthly using available information at the time to answer budget and operation management immediate needs. As such, information could be biased and the data-driven VFM models are used to provide alternative allocations at each wellhead level to improve the confidence in reservoir history matching.

The paper presents successful use cases of such data-driven VFM built within the tool TDASH developed by the Company as part of its Digital Transformation Roadmap providing reservoir and production engineers friendly access to Artificial Intelligence means through a no code/low code approach.
Revolutionizing Leak Detection and Cost Savings in Valve Predictive Maintenance
Authors: Al Ruqaishi Mahmood Ahmed , Al Kalbani Fahad Khamis
Published: November 2024

valves are essential components of safeguarding and control systems, playing a crucial role in ensuring that plants operate efficiently and safely. Valve failures can lead to significant production losses, increased maintenance (operating) costs and contribute to process safety incidents. In plants, a common technique for valve maintenance is condition-based replacement at fixed time intervals. Evaluating the condition of in-service valves that process fluids present substantial challenges, particularly when diagnostic methods requiring valve movement are impractical during plant operations. This limitation complicates future maintenance planning, often forcing maintenance teams to either schedule potentially unnecessary valve work for upcoming shutdowns or forego maintenance entirely. Delaying maintenance can lead to costly, unplanned maintenance activities, unplanned shutdowns, and operational deferments, with the associated loss of production often far exceeding the maintenance costs. To address these challenges, the use of Acoustic Emission (AE) techniques is proposed for valve condition assessment. AE techniques offer a non-intrusive and effective method for monitoring the integrity of in-service valves without requiring operational disruptions. By detecting the high-frequency waves generated by crack growth, leakage, or other structural changes within the valve, AE techniques can provide real-time diagnostic information, enabling more accurate maintenance planning and preventing costly unplanned events.

This innovative approach aims to improve the reliability and efficiency of valve maintenance schedules, reduce unnecessary maintenance activities, and minimize the risk of unplanned shutdowns. The integration of AE techniques into valve condition monitoring represents a significant advancement in maintenance strategy, offering a more proactive and informed approach to ensuring the operational integrity of fluid processing systems. Hence, this paper aims to examine the effectiveness of the Acoustic Emission technique in detecting early leakage in safety and control valves when they are fully closed on-site. With an investment of around $20K in a small portable measurement device and utilizing cutting-edge Acoustic Emission technology, this project markedly reduced saleable gas loss. Achieving substantial progress toward our zero-emission objective, improving the overall maintenance cost and strategy and also slashed shutdown times by 70% while maintaining plant integrity and availability.
Advances in High-Performance Computing for Static and Dynamic Modelling
Authors: Kamashev A. , Azagbaesuweli G. , Sudiro H. , Al-Jenaibi F. , Bogachev K. , Gusarov E. , Kuzevanov M. , Kostin G. , Shimonin E.
Published: November 2024

In recent years, the oil and gas industry has increasingly leveraged high-performance computing (HPC) to tackle complex reservoir simulations. These simulations are crucial for understanding subsurface conditions, optimizing hydrocarbon recovery, and ensuring efficient resource management. Among the various simulation techniques, compositional modeling stands out due to its ability to capture detailed fluid behavior and interactions within the reservoir. This type of modeling is particularly valuable for predicting the behavior of multi-component fluid systems, which are common in many reservoirs.

One of the primary challenges in compositional modeling is the need for high-resolution grids. High-resolution grids enable more accurate representation of geological features and fluid dynamics but come with significant computational demands. As the resolution increases, so does the number of active grid cells, which can quickly escalate into the billions. Managing such large-scale models requires not only advanced software capable of handling vast amounts of data but also powerful hardware to process and visualize the results efficiently.

This study focuses on the development and implementation of a high-resolution compositional dynamic model with almost half billion active grid cells. The primary aim is to explore the capabilities and limitations of current software and hardware in managing these large-scale models.
Expandable Liner Hanger Installation in Middle East Exploration Well - South Arabic Gulf Offshore
Authors: Khadr M. , Williford J. , Osama M. , Palumbo D. , Saragih N.
Published: November 2024

This document will capture the experience of Expandable Liner Hanger successful installations for an Offshore Exploratory Well in South Arabic Gulf considered the first well profile in the Area to contain 4 different cemented Liner sizes starting from 16" Liner to 9-5/8" (with possibility of 2 contingency Liner Sizes 7" & 4-1/2").

In a challenging sour environment and complicated well design, the Expandable Liner Hanger system was selected as a proven reliable technology recognized worldwide.

The document will discuss the challenges in design and execution phases to reach the required TD of the well, exceeding 20,000 ft, to explore 2 main 4 ways structural closures. Liner Hanger implementation in the well was a key point to reach the required depths without jeopardizing the well design.

Procedures to run, install and cement the expandable liner hanger in place capturing all lessons learned and implementing the required risk assessments was a result of collaboration between engineering and operation teams to plan and prepare for all contingencies resulting in a smooth execution.

Expandable Liner Hanger helped to set and cement all casing shoes at planned depths in a complex well design offering a high capability of reaming while encountering high Pressures, high flow rates & high torques with no risk for premature release or premature set which is not feasible with a Conventional Liner Hanger system.

16"x20" Liner was installed through multiple kicks overcoming more than 75 tight spots (either with SOW, rotation or ream down) and cemented.

13-5/8"x16" Liner with single trip tieback system - designed and built for the project - that enabled minimizing the large OD length of the hanger system in 13-5/8″ × 16″ whilst also providing the tieback operation flexibility through a 20ft stroke system to surface was successfully installed.

13-3/4"x13-5/8" faced Intensive reaming down for more than 48 hours while slacking off all Liner weight & facing high torques with high flow rates/pressures. Finally, 9-5/8" Liner and 20 ft tie back to surface was successfully installed.

Utilizing the Expandable Liner Hanger as a reliable system in such challenging well allowed us to exploit all its potential. Continuous Improvements in Planning through execution phase within the simulations (Torque and Drag, Surge & Swab, wellCat simulations) and in the rig installation procedures resulting to mitigate risks and providing improved reliability, enhanced operational capabilities, and well integrity assurance.