bluuebunny/crossref_metadata_2025 huggingface dataset:
Acoustic Anti-Scaling Technology for Sustainable Scaling Prevention in the Oil and Gas Industry
Authors: Al Munif E. H. , Alhamad L. A. , Almubarak T. A.
Published: October 2023

Scaling in the oil and gas industry is a common problem that increases expenses and reduces production rates. Traditional methods of scale prevention include chemical treatments that can be expensive and have environmental implications. Acoustic anti-scaling technology is an alternative method that has gained attention in recent years. This paper provides an overview of acoustic anti-scaling technology, including its principles, applications, and limitations. The paper concludes by discussing the potential for further research and developments in this area.

This review includes various laboratory studies that evaluate the potential of using acoustic anti-scaling technology in scale removal applications. A comprehensive literature review was conducted. Acoustic anti-scaling technology was also compared to mechanical and chemical scale treatment solutions currently used by the industry.

Acoustic anti-scaling involves the use of ultrasonic waves to disrupt the formation of mineral scale deposits. The ultrasonic waves create high-frequency vibrations that prevent mineral particles from attaching to surfaces and forming a solid scale layer. Typically, the frequencies used for anti-scaling are in the range of 20 kHz to 100 kHz, although some systems may use higher or lower frequencies depending on the specific equipment, composition of the fluids and the desired level of scale prevention. Acoustic anti-scaling technology has been shown to be effective in reducing scaling in various industrial systems, including desalination plants and cooling tower systems. For years, chemical and mechanical treatments have been implemented effectively to achieve scale removal and prevention. Water consumption, cost and environmental concerns have been associated with these methods.

The review also highlights some limitations of acoustic anti-scaling technology. The technology is most effective in preventing the formation of soft scale, such as calcium carbonate. However, it may not be as effective in preventing hard-scale formation, such as barium sulfate. The effectiveness of the technology may also be limited by factors such as water chemistry, flow rate, and temperature. Therefore, further research is needed to optimize the technology's performance under various conditions.

The paper provides novel information by analyzing the available literature on traditional scaling prevention methods and acoustic anti-scaling technology, and identifying the current state of research in this field. It also highlights the potential of acoustic anti-scaling technology as an environmentally friendly and cost-effective alternative to traditional methods of scaling prevention in the oil and gas industry.
In Field Referencing Study by Drone Aeromagnetic Measurement
Authors: Wiharja A. , Jufrihadi J. , Sany M. F. , Gunawan F. , Pribadi M. , Macresy L. , Momot F. , Sikal A. , Harbidge P.
Published: October 2023

Relief well drilling plays a crucial role in mitigating uncontrolled well incidents, ranging from minor well-control events to catastrophic blowouts. Achieving accuracy in drilling a relief well, particularly in intercepting a small target or re-entering an uncontrolled well casing, is of paramount importance. To ensure success, advanced survey management techniques are essential for precise relief well and target well positioning. Among various techniques, conducting an In Field Referencing (IFR) acquisition has proven to have a significant impact on reducing well lateral uncertainties by accurately determining the local geomagnetic field and its crustal anomalies.

In the context of relief well drilling operations, achieving timely and effective In Field Referencing (IFR) is key due to the time constraint. This paper focuses on the chosen method of deploying a drone from an offshore barge in order to conduct the IFR, highlighting its efficiency and effectiveness. The utilization of a drone enables rapid deployment and data acquisition, contributing to significant time savings. Additionally, the offshore barge serves as a stable platform, facilitating precise positioning and data collection during the IFR procedure.

Notable advantages of IFR acquisition include fine-tuning target well positioning through IFR and Multi Station Analysis (MSA), reduced lateral uncertainty of the target well, enhanced quality control thresholds for MWD data, accurate calculation of azimuth using IFR-corrected declination, increased chances of target well detection during the locate phase, improved interference detection from the target well, and enhanced interception efficiency with robust HSE management.

This article presents a comprehensive study on the implementation of IFR during the planning phase of an offshore relief well project in an offshore field. It covers various aspects, including mobilization, acquisition set-up, methods employed, procedural considerations, and the obtained results. By shedding light on the IFR process, this study aims to contribute to the knowledge and understanding of advanced survey management techniques in relief well drilling operations.
Leveraging Condition Based Major Overhaul for Higher Uptime and Profitability
Authors: Al-saedi Khaled , Al Awadhi Hesham , Kalhoro Muhammad U Ddin , Nadeem Muhammad , Al Harmi Sultan , Al Halabi Saleh
Published: October 2023

ADNOC's smart growth strategy necessitates all entities to maximize efficiency and profitability through transformation of business strategies and embracing the latest technologies. In oil and gas operations, major overhauling of rotating equipment is one of the main contributing factors to increasing operating cost and plant availability. However, to ensure the integrity and reliability of rotating equipment, a cost-effective maintenance strategy must be applied over the asset life cycle. In the pursuit of this objective, ADNOC Onshore Bu Hasa team worked towards optimization of major overhaul maintenance adapting a holistic approach for rotating equipment through transformation of maintenance overhauling strategy from traditional time based to condition-based overhaul. The condition-based maintenance overhaul strategy is based on accurate thermodynamic performance monitoring combined with physical condition assessment that was achieved through a customized digital solution.

Condition-based overhaul strategy was applied mainly on three different types of equipment that includes large size process pumps (centrifugal), special type Helico-axial design Multiphase pumps and centrifugal gas compressors. As a first step, revised overhaul strategy applied on water injection pumps (high pressure multistage centrifugal pumps) considering its impact on recurring maintenance cost and scheduled down-time, as on average 6 to 8 units become due for major overhaul each year based on meter-based frequency. And gradually condition based overhaul strategy was extended to other large size process pumps such as multiphase pumps and centrifugal gas compressors.

Through the transformation of maintenance major overhaul strategy for rotating equipments based on accurate condition assessment and evaluation, achieved a significant cost saving up to 30%, increased uptime by 15% extending overhaul interval based on accurate health assessment and utilizing specialist independent service providers with service base in the country and hence contributing to In-Country value (ICV) targets.

The paper provides proven case study with examples of different types of rotating equipment where condition-based major overhaul was successfully deployed and adopting similar maintenance overhaul strategy for rotating equipment will help in achieving significant cost optimization over life cycle and maximize plant availability.
The Potential CEA/CCER Market Value for Natural Gas+ System: An Assessment Using the Logistic Growth and Technology Transfer Model
Authors: Ye Xiong
Published: October 2023

China has committed to achieving carbon peak and neutrality targets, and ETS serves as a major and innovative policy instrument, which consists of both Chinese Emission Allowances (CEAs) and Chinese Certified Emission Reduction (CCER). Considering the appeal for restarting CCER market, this paper proposes the "Natural Gas+" CEA and CCER techno-economics system and establishes the potential market value evaluation model for corresponding CEA and CCER. By exploring the combination scenarios among revised carbon emission, Natural Gas consumption, market shares of different phases’ technologies and carbon prices, the reasonable potential market value range of the "Natural Gas+" system for CEA and CCER are obtained. The potential market value of CCER is rising year by year with range of 669.2~1367.6 billion yuan in 2050, displaying a median value of 1031.1 billion yuan without outlier. Nevertheless, the CEA market value will reach peak in 2048 with range of 71.5~162.1 billion yuan, performing extremely large outliers from 2030. The results could quantitatively support the policy recommendations for restarting the CCER market.
Innovative Practice and Development Countermeasures of Oil and Gas Cooperation Along the Belt and Road with the Background of Carbon Neutrality
Authors: Li Changyong , Tong Yi , Jiang Junshuai , Na Risu , Da Lina
Published: October 2023

Considering the current status of China's energy mix, requirements for the energy transition and the development level of renewables, oil and gas will play an essential role in China's long-term energy supply, with its proportion in the primary energy consumption accounting for around 30% until 2040. The goals of "carbon peak" and "carbon neutrality" put forward higher requirements for international cooperation in the oil and gas sector along the Belt and Road (B&R), together with low carbon development. Chinese state oil companies, represented by PetroChina, Sinopec and CNOOC, actively participate in the Belt and Road Initiative (BRI), collaboratively operating many world-class oil and gas development projects, as well as technological innovation and practice. The annual oil and gas equity production from these cooperation projects exceeds 200 million tons of oil equivalent, which weighs heavily in the international energy cooperation, and accelerates the energy transition. With the background of carbon peak and carbon neutrality, fossil fuels remain of critical importance to the current energy system. Cooperation in oil and gas along B&R faces unprecedented opportunities, multiple environmental supervision and carbon emission reduction pressure.

In view of above situation, countermeasures to the development in oil and gas along B&R are put forward: 1) strengthen the cooperation and development in oil and gas along B&R to enhance the international energy cooperation, natural gas production and utilization, and accelerate the energy transition to diversify China's energy mix; 2) improve energy use efficiency and optimize energy use in exploration and development system, strengthen the construction of intelligent oil fields and shore power, and implement decarbonizing measures throughout the industrial chain to increase the pace and extent of energy conservation and emission reduction; 3) actively develop carbon-negative technologies and infrastructure, and promote carbon capture, use and storage (CCUS) application represented by carbon dioxide flooding, water alternating gas flooding etc., gradually shifting to a lower carbon energy system; 4) promote the integrated development of traditional resources and alternative energy, open channels of financial support, technology and talents, actively deploy new energy business, and coordinate the development of non-fossil energy industries such as solar energy and wind power.
Estimating the Effects of Wag-EOR on Elastic Properties for Seismic Reservoir Monitoring in Abu Dhabi
Authors: Mohamed M. , Ahmed J. , Mahmood H. , Aljaberi A. , Waqas M. , Alhamedi A. , Mouri T. , Shimizu H. , Yamada Y. , Mochizuki M.
Published: October 2023

When implementing CO2 WAG EOR, fluid distribution and pore pressure in the reservoir vary. The interpretation of seismic reservoir monitoring for WAG-EOR often includes uncertainty in the changes obtained by time-lapse seismic surveys because these changes are the integration of effects by several factors. The objective of this study is to estimate the impact of each factor on elastic property and investigate a dominant factor through a rock physics study at a CO2 WAG site in Abu Dhabi.

To estimate the effect of pore-pressure change on elastic velocity, an empirical relation between elastic velocity and confining pressure was used. Sonic velocity using core plug samples of the reservoir was measured under multiple confining pressures to construct empirical relations. As for the effect of fluid saturation changes on elastic velocity, we estimated it through Gassmann's equation. Realistic changes in pore pressure and saturations during the WAG operations were based on reservoir simulation results. Finally, based on the input petrophysical data and the relations from rock physics analyses, elastic property changes in WAG-EOR are estimated.

Density and P-wave velocity (Vp) changes caused by the fluid substitution from oil to water are more significant than those by the substitution from oil to CO2. Pore pressure changes have less of an impact on Vp variations than does fluid substitution. Based on the estimation of elastic property changes associated with WAG operations, density changes are affected mainly by the increase in water saturation because of the density difference between water, oil and CO2. Vp changes seem to be consistent with the increase of gas (CO2) saturation. Even in the upper zone of the reservoir where oil is swept by both injected water and CO2, the effect of CO2 is prominent as well-known low gas saturation effects. Vp is significantly affected by the small amount of CO2 which was observed in the comparison of Vp with and without 10% of CO2 saturation in the rock. P-impedance changes are consistent with Vp changes because of the larger changes of Vp than the density changes. From these observations, the changes obtained by seismic reservoir monitoring would mainly represent the effect of CO2 saturation changes.

We quantitatively looked into the impact that changes in pore pressure and saturation had changes on elastic properties such as density and elastic velocity. Furthermore, it was determined which elements predominately control changes in elastic properties when these changes occur simultaneously in WAG-EOR operations. These findings play an important role in the interpretation of seismic reservoir monitoring for WAG-EOR in Abu Dhabi.
From Pixels to Insights- Harnessing the Power of Deep Learning for Facies Classification in Borehole Images
Authors: Mukherjee S. , Jiang X. , Al Ka'abi M. , Khan M. , Kherroubi J.
Published: October 2023

The objective of this study is to develop a deep-learning-based framework for automated facies classification in borehole images. We aim to address the limitations of manual facies classification, including subjectivity, errors, and time consumption. The framework should be efficient, accurate, and easily integrable into existing workflows in the oil and gas industry.

The study uses deep-learning techniques, specifically convolutional neural networks (CNN), to develop a model for feature extraction and classification. The model employed is the state-of-the-art, open-source EfficientNetB4 architecture. The study also employs data preparation techniques, such as data augmentation and Synthetic Minority Over-sampling Technique (SMOTE) to handle labelled data set class imbalance.

The study involves three main steps: data preparation, model training, and evaluation. In the data preparation step, borehole images are processed into pixel-level data, sampled at a particular resolution, labelled, and augmented. In the model training step, the model is trained on the labelled data set using the EfficientNetB4 architecture. The evaluation step involves measuring the accuracy and F1 score of the model to analyze its performance.

The results demonstrate the effectiveness of the proposed framework, achieving an accuracy of 85% on the test data within minutes. The study also shows that the model can generalize well to variations in image quality and resolution, indicating its robustness and potential applicability in real-world scenarios.

The study highlights the potential of deep learning for automated facies classification in borehole images, providing a more objective, accurate, and efficient approach to subsurface characterization. The use of artificial intelligence (AI) and analytic platforms enables efficient integration of the framework into existing workflows, supporting decision making in the oil and gas industry.

The study demonstrates that deep-learning-based frameworks can offer valuable insights for the oil and gas industry, enabling improved resource management and accelerating project delivery. The proposed framework provides an objective and efficient approach to facies classification, overcoming the limitations of manual techniques. The study also shows the potential for the framework to be applied to other image classification tasks in the oil and gas industry.
How to Properly Place a Scale Inhibitor Squeeze Treatment?
Authors: Rafie M. , Almubarak T. , Alotaibi F. , Alsunnary K.
Published: October 2023

When oil producers start producing water, a variety of issues arise. This includes decline in oil production rates, corrosion, emulsion, and is coupled with inorganic scale precipitation. One common treatment in such scenarios is a scale inhibitor squeeze. Scale inhibitor squeeze treatments are very effective and can prevent precipitation of scale during production for an extended period of time. This work will discuss the lab and field tests required for a scale inhibitor squeeze job in an oil producer.

Compatibility tests between the scale inhibitor and the downhole fluids were conducted using static lab experiments and an inorganic scale prediction software. Additionally, HPHT coreflood was utilized to determine the compatibility between the scale inhibitor squeeze treatment and the downhole rocks at 200°F. Moreover, thorough well completion components, completion settings, mineralogy, and productivity indices were assessed before and after the scale inhibitor squeeze job.

The results showed that the scale inhibitor squeeze treatment worked as intended, exhibiting no incompatibility issues between the used scale inhibitor and the downhole rocks or fluids such as downhole oil and downhole water. However, it was noted that when the amount of scale inhibitor was excessive in the coreflood tests, it produced significantly higher precipitation at the core inlet which led to an increase in pressure drop. Consequently, bullheading excessive amounts of scale inhibitor is not recommended. Following this analysis, a carefully controlled scale inhibitor squeeze is advised through a coil tubing targeting the zone of interest where the inhibitor was intended to be used.

This work shares the tests and the analysis that needs to be done to successfully place a scale inhibitor squeeze job in an oil producer. This study proved that a full understanding of the well components, fluids, and rock properties is critical.
Artificial Intelligence-Assisted Seismic Mapping of Mediterranean Complex Turbidite Reservoirs Depositional Architectures for Effective Gas Exploration and Development
Authors: Hafez Ahmed , Castagna John
Published: October 2023

Accurate mapping of internal depositional architectural elements of a Pliocene-aged gas-bearing turbidite reservoir of the Mediterranean Basin into discrete 3D geobodies has been achieved through applying innovative workflow assisted by the convolutional neural network. The mapped reservoir depositional architectures have been integrated to the acoustic and elastic properties inverted form 3D seismic data to build robust multi-realizations reservoir static models. These models have been used to optimize the appraisal and development well locations and accurately assess the gas initial in-place of the discovery. Four wells have been sited utilizing the results of the constructed models. The wells have been successfully drilled and added 175 Million standard cubic feet in a day (MMscf/d) which obviously improve the commercial value of the project. The workflow is a major step in accurate delineation of the internal depositional architectural elements of the deep-water turbidite reservoirs of the Mediterranean Basins, as well as in other locations/basins where similar settings exist. By applying the workflow, the subsurface complexities were revealed with the artificial intelligence algorithms, uncertainties were captured, risks were reduced and project commercial value was uplifted.
Operational Pigging Prediction by Machine Learning
Authors: Ramlan M. , Khabri K. A.
Published: October 2023

The paper demonstrates how Operational Pigging frequency is optimized to minimize production deferment and achieve Operational Excellence by predicting the required frequency via machine learning based on the operating condition of the pipeline. Currently, the Operational Pigging frequency is fixed at 3-monthly which leads to 4 times the production deferment required in a year to allow for the Operational Pigging activity to be executed.

To perform this prediction, historical data of the pipeline from 2016, which consists of oil flow rate, gas flow rate, running time, water content, and previous operational pigging record,areobtained, and analyzed. From the data, patterns and trends are developed to understand the influence of each data on the prediction model. The data is split into a 60:40 ratio where 60% of the data is used to train the machine learning model, and the remaining 40% of data is used to test the trained model.

Based on the historical data obtained, the pigging debris is selected as the target outcome of the machine learning prediction. The trained model using Poison Regression Model upon evaluation shows good accuracy and is able to predict the debris to be collected from the Operational Pigging activity. The prediction of the pigging debris reveals that the Operational Pigging activity frequency can be prolonged fromthe established frequency of 3-monthly to a bigger frequency of as much as 1-year frequency while the debris collected will still be within the acceptable limit. This ultimately allows the operator of oil field ‘K’ in Middle Eastto reduce production deferment as the number of Operational Pigging required in a year is reduced with this prediction.

From an Operational Excellence perspective, this prediction model provides a solution to minimize production deferment while ensuring the integrity of the pipeline is not jeopardized.
Unsupervised Multitask Learning for Oil and Gas Language Models with Limited Resources
Authors: Marlot Maxime , Srivastava Divya Nidhi , Wong Fui Kent , Lee Ming Xiang
Published: October 2023

In this paper we explore the development of an oil and gas language model (LM) using an unsupervised multitask learning approach. A large language model (LLM)enables computers to understand and generate human language. The study addresses data scarcity and domain-specific language challenges, showcasing the model's performance on specific oil and gas tasks and qualitative testing. To do that, we collected a highly diversified dataset of 33,000 documents in energy and oil and gas domains to train and benchmark our model.Our findings demonstrate that even a small model, properly finetuned on domain-specific data, outperforms larger models trained on generic corpora, highlighting the benefits of finetuning LMs in technical domains. The paper contributes to advancing natural language processing (NLP) in the oil and gas industry, emphasizing the importance of addressing domain-specific nuances and limitations for improved NLP model performance and reliability.
Effective Utilization of Innovative Sand Screen Technology for Resolving Water Injection Challenges: A Case Study of Field X in Nigeria
Authors: Ngerebara Justus , Alawode Olusiji , Moradi Mojtaba
Published: October 2023

Numerous technologies have been deployed to improve the structural integrity and long-term efficacy of injection wells, ultimately enhancing oil recovery within a designated Nigerian field.

Thorough data analysis has indicated that the presence of formation solids arising from occurrences such as water hammer, backflow, and crossflow represents a substantial challenge to the integrity of multiple injection wells in the targeted field. This challenge is particularly pronounced when fines migration and accumulation within the lower completion take place during abrupt or extended well shut-ins. Although these formation solids generally reside within the reservoir during steady injection, they can be mobilized into the wellbore during rapid shut-ins due to the powerful transient flow effects of water hammer, cross flow, and backflow. This can lead to elevated bottom hole injection pressure (BHIP), reduced or lost injectivity, screen blockages, and erosion of downhole equipment. In turn, this may compromise the ability to sustain pressure support for producer pairs, potentially necessitating interventions, remediation, sidetracking, or wellbore abandonment. Alternative technologies previously applied in these wells have proven ineffective for a variety of reasons.

In light of these challenges, the novel NRV screen technology specifically developed for such projects was identified as the optimal solution from a range of available alternatives, based on a matrix of requirements for the new campaign. This technology, designed to be installed closest point to the sandface, was selected for its capacity to autonomously and immediately isolate the reservoir from the wellbore during shut-ins, its non-obstructive nature for intervention tools, its unhindered access to the lower completion sandface during injection and intervention, its durability throughout the well's operational life, compatibility with openhole standalone screen (OH-SAS), gravel pack (GP) completions, and direct wrap or metal mesh screens, as well as its cost-effectiveness compared to other options.

The performance data from the wells demonstrated that this innovative completion technology has effectively achieved the targeted rate and desired performance thus far, providing the Field X team with a robust solution to mitigate prevalent challenges in injection wells while avoiding the need for costly interventions.

Presently, the technology has been successfully implemented in three wells. This paper presents the pre-qualification studies, the comprehensive qualification test outcomes, and the subsequent post-installation performance of the wells. Also, the lessons learnt from these installations are shared.
Sustainable Economic Strategies for Corporate CEOs: AI-Driven Leadership in Driving Innovation, Growth, Safety, Sustainability, and Climate Change Resilience to Save Lives and Our Planet -A Comprehensive Comparative Policy Analysis on Unlocking Pakistan's Geothermal Potential
Authors: Aun Ali Syed Muhammad , Zaidi Syeda Fardees , Louis Clifford , Anjum Muntaha , Ali Syed Imran , Haneef Javed , Lalji Shaine Muhammadali , Ahmed Shabeer
Published: October 2023

This research investigates pressing need for sustainable practices, and examines the current state of geothermal energy development in Pakistan, despite its significant untapped potential. Through comparative analysis of policies and regulations prevalent in geothermal-rich nations like Iceland, the United States, and Kenya, valuable insights emerge. These insights can provide a roadmap for promoting geothermal energy growth within Pakistan.

Furthermore, the paper discusses about sustainable economic strategies tailored for corporate CEOs, centered around AI-driven leadership. It also illuminates the potential of artificial intelligence in steering innovation, promoting growth, enhancing safety measures, ensuring sustainability, and fortifying climate change resilience. By harnessing AI's capabilities, corporate leaders can play a pivotal role in safeguarding lives and the planet.

In addition the research addresses upon utilizing a comparative policy analysis methodology. The study evaluates institutional frameworks and arrangements of leading geothermal nations. By identifying challenges and opportunities specific to geothermal energy advancement in Pakistan, the research suggests strategic steps for progress. These include the formulation of regulatory frameworks, provision of investor incentives, and support for research and development. The study's outcomes contribute to energy security and sustainability, while its innovative perspective serves as a benchmark for Pakistan's geothermal initiatives. Moreover, these findings extend to other countries aspiring to harness their own geothermal resources.
Integrated Approach for Effective Asphaltene Precipitation and Deposition Detection in Greenfield Wells
Authors: Lee W. , Hamza M. , Shim J. , Mogensen K. , Grutters M.
Published: October 2023

This paper presents a comprehensive approach for assessing asphaltene precipitation and deposition in greenfield wells, which includes asphaltene risk evaluation using stock tank oil and bottomhole oil with and without miscible gas injection, the development of an asphaltene deposition simulation model employing PROSPER, and the interpretation of well operation results.

A holistic solution for assessing asphaltene deposition in greenfields is proposed by combining laboratory analysis, simulation models, and field data. The methods involve screening techniques using dead oil, such as SARA plot, De Boer plot, CII index. These preliminary results were complemented with AOP tests using live oil and field intervention outcomes to confirm the risk. A throttle model was developed to estimate asphaltene deposition in wellhead throttle valves, validated using wellhead choke inspection and well test data.

The comprehensive approach to managing asphaltene deposition in greenfield proved effective, as demonstrated by the results. The asphaltene risk assessment, well intervention activity interpretation, and simulation model successfully identified high asphaltene risk wells and targeted asphaltene treatment locations. Various screening methods determined different levels of asphaltene risk, with one method selected after comparison with AOP and field observations as the screening technique for new wells and reservoirs. Based on screening, asphaltene envelopes, and the deposition model, eight wells were chosen for asphaltene treatment.

This paper offers unique insights by introducing a comprehensive approach for detecting asphaltene deposition in greenfield wells. The novel wellhead choke model, in particular, enables a simple prediction of asphaltene deposition using existing wellhead parameters and well test data. The findings have significant implications for greenfield management and can be applied to other oil-producing regions globally.
Improved Up-Down Deconvolution in Ultra-Shallow Waters Offshore Abu Dhabi
Authors: Mahgoub M. , Cambois G. , Domont S. , Nassar T.
Published: October 2023

The ultra-shallow water-depth and hard water bottom of offshore Abu Dhabi are responsible for generating a complex multiple wavefield. Removing this energy is critical for accurate imaging of the subsurface. Almheiri et al. (2022), demonstrated the effectiveness of up/down deconvolution to attenuate multiple energy on Ocean bottom sensor (OBS) data from offshore Abu Dhabi. In this paper we detail recent advances to this workflow, leading to enhanced imaging results from offshore Abu Dhabi.

Amundsen (2001) showed that deconvolving the up-going wavefield by the down-going wavefield produces an estimation of the Earth's reflectivity series. While this technique gives a step-change in demultiple results from OBS data offshore Abu Dhabi, it suffers from high noise levels – particularly in the higher frequencies. Advances in linear noise removal enable the attenuation of mud-roll from the input data without harming the water-wave – an essential ingredient to up/down deconvolution. Removal of the mud-roll consequently enables better attenuation of shear-wave noise from the vertical geophone component.

The advanced workflow leads to improved wavefield separation and superior data for up/down deconvolution.The advanced pre-processing flow was applied to an OBS dataset from Offshore Abu Dhabi and used as input to up/down wavefield deconvolution. The up/down deconvolution results were benchmarked against a previous result from the same OBS dataset, without the application of the improved pre-conditioning flow. Reverse time migration (RTM) imaging using both datasets showed a clear improvement in signal-to-noise ratio on the new results, with improved reflector focusing, especially at the reservoir target level. Frequency band splitting showed better phase alignment across the bandwidth in the new data compared to the legacy results.

These results confirm that advanced de-noising techniques, allowing for the removal of high-amplitude mud-roll and shear-wave noise, without harming the water-wave, refraction energy or primary reflections, leads to improved wavefield separation and consequently improved up/down deconvolution results. The improved results exhibit reduced noise content, better event focusing and improved phase alignment across the frequency spectrum.
PSM Evergreening with Artificial Intelligence
Authors: Casal A.
Published: October 2023

Several "ad-hoc" safety assessments are routinely performed in Major Hazard Facilities such as Operational Risk Assessments (ORA), Management of Change (MOC) HAZOPs, Pre Startup Safety Reviews (PSSR), maintainability reviews and Root Cause Analyses (RCA). Recurrent safety assessments include HAZOP revalidations (re-HAZOPs), Safety Case / Safety Reports, BowTie reviews, etc. Undertaking these assessment in a coherent and systematic manner is problematic, not to mention keeping all the safety related information updated and in the same place.

This paper describes how Artificial Intelligence (AI) can be used to build and maintain a "live" functional twin of any industrial facility where Process Safety (PS) information is continuously updated and accessible to support standard risk management processes, which is the basic feature underpinning the concept of "Process Safety Management (PSM) evergreening". Employing Multilevel Flow Modelling (MFM), a functional twin of the facility is created by the HAZOP Assistant software application. With its reasoning capability, the model creates a map of all possible causal-effect relationships, linking causes with end consequences and safeguards alike a HAZOP study or a bowtie. This "live" map of causal-effect relationships can be accessed and displayed at any time in the form of an event tree or bowtie. The functional twin is not a database of words but an actual physical model which includes qualitative mass and energy balances. As PS knowledge improves, the model can be easily updated with the new information. When changes are made to the facility, the model can be updated to reflect the "as-is" status, so that safety assessments are updated and relevant.

The paper highlights how the HAZOP Assistant software application builds and maintains a functional twin of the facility to support the above processes consistently and efficiently, in one platform and reducing errors and costs.
Enhancing Structural Imaging and Well Data Integration with OBN 4C Data: Addressing Geological Uncertainties in Complex Deep Reservoirs
Authors: Ramli A. H. , Munif H. A. Ahmad , Zulkifli N. F. M , Bakar H. H. Abu
Published: October 2023

Objectives/Scope: The primary aim of this study is to illustrate the substantial advantages of utilizing Offshore Bottom Nodes (OBN) with four components (4C) for enhancing seismic image quality, thereby offering improved input for both static and dynamic models. Furthermore, the findings have proven instrumental in resolving long-standing discrepancies regarding fluid contacts in Field A.

Methods, Procedures, Process: The approach employed in this study involved a combination of well-established acquisition parameters and the implementation of a novel imaging algorithm, primarily the Full Waveform Inversion (FWI). By optimizing the acquisition setup, we achieved enhanced imaging of deeper zones, effectively reducing structural uncertainty and providing greater clarity on the structural shapes within these areas. Additionally, this approach facilitated improved continuity of amplitude in the presence of shallow gas. Fluid contact analysis at the well level was conducted by integrating log data, mud logs, pressure points, and production history for each well. Structural comparisons were also performed to highlight the notable differences in image quality when compared to traditional APSTM seismic images.

Results, Observations, Conclusions: The findings of this study demonstrate that fluid contact values, as determined through well logs, now align with the updated structural understanding of faulting and compartmentalization. This has led to enhanced structural interpretation, featuring more distinct fault imaging and partial resolution of shallow gas issues. The presence of shallow gas in previous seismic data resulted in the appearance of structural anomalies, causing images to depict sags as faults. With the new seismic images, multiple sand body pinch-outs were more readily identifiable, and boundaries were captured with greater clarity due to the higher resolution. Additionally, the generated Root Mean Square Attribute (RMS) significantly contributed to determining Field A's geological body, enabling accurate facies distribution across the field.

Novel/Additive Information: This study's innovative approach has yielded valuable insights, primarily stemming from differences in seismic acquisition techniques. The previous dataset employed a streamer method, whereas the latest dataset utilized an OBN (Ocean Bottom Node) approach. The new dataset features a more advanced seismic imaging technique, leveraging full-waveform inversion. The key lesson learned is the importance of continually updating interpretations based on the most current datasets, whether they are obtained through reprocessing or re-acquisition of data.
Novel Method to Calculate Free-Gas-Filled Porosity for Shale-Gas Reservoir and Production Prediction Using Wireline Nuclear Magnetic Resonance: A Case Study in Sichuan Basin, China
Authors: Rui Yun , Wang Yue , Niu Wei , Zhao Xian Ran , He Ye , Li Hui Geng , Shi Yang Zhi , Wu Jin Long , Pan Feng , Li Kai Xuan , Xu Lei
Published: October 2023

The performance of shale-gas wells varies significantly from well to well, and free-gas volume dominates the initial testing production of shale-gas wells. The uncertainties in pore-pressure estimation will lower the accuracy in quantifying the free-gas-filled porosity of shale-gas reservoirs, which translates into high uncertainties for the overall formation evaluation. Therefore, it is necessary to incorporate other methods independent of pore pressure for the free-gas calculation.

In this paper, the authors present a customized shale-gas formation evaluation workflow that integrates core analyses and wireline logging data. The pore fluid of the shale-gas reservoir is a mixture of free gas, adsorbed gas, and water. The hydrogen index and density of the free gas are different from those of adsorbed gas and water. The free gas, adsorbed gas, and water-filled porosities can be quantified when nuclear magnetic resonance (NMR) and triple-combo logs are incorporated, using an iterative method. A robust methodology integrating free-gas ratio (FGR) and other wireline measurements shows great advantage in shale-gas production prediction.

Case studies are presented from the shale-gas reservoirs of Taiyang and Daan Blocks in PetroChina's Zhejiang Oilfield. These case studies incorporate wireline-induced gamma ray spectroscopy, NMR, borehole images, dipole sonic measurements, and some special core measurements. The core NMR experiment and ion-milled backscatter scanning electron microscope indicate that the organic pore size ranges from 3 to 42.3 nm, the inorganic pore size ranges from 16.8 to 42.3 nm, and the ratio of organic pores to inorganic pores is about 2.5:1. The quantification of free gas, adsorbed gas, and water-filled porosities proves to be successful. The FGR varies in different wells. It is usually higher than 50% in the reservoir, and it can reach more than 80% in the sweet zone. Wells with high FGR prove to have promising gas production. Wells with abundant fractures and high formation dip angle prove to have low gas production. The core-validated petrophysical properties of lithology, porosity, permeability, total organic carbon content, gas content, water saturation, and triaxial stress magnitudes alleviate the uncertainties in determining the best zones.

In this paper, a novel application of core-validated formation evaluation of shale-gas reservoirs is discussed, which helps the operator ascertain the potential for future development. The FGR shows a good match to the gas production. The workflow can be applied to other shale-gas plays in China.
Novel NFDM Workflow: An Approach to NMR Data Processing for Accurate Fluid Typing and Saturation Determination
Authors: Gao J. , Kwak H. T. , Boudjatit M. , Althaus S. , Chen J. , Sørland G. H.
Published: October 2023

Accurate fluid typing and quantitative saturation determination are essential to evaluate reservoir production potential, which is a well-known deliverable by NMR measurements. However, challenges remain in obtaining these critical reservoir properties due to the ill-posed nature of Inverse Laplace Transform (ILT)-based NMR data processing and partitioning of overlapping continuous T1/T2 or 2D T1T2 distributions. This work presents a straightforward and efficient data processing workflow, the NMR fluid discretization method (NFDM), based on a new discrete inversion method, Anahess.

The first step in existing NMR data processing and interpretation is to apply the ILT methods with known issues of spurious peaks and broadening at the short relaxation time region. The overlapping peaks in 1D and 2D continuous distributions reflect the continuous oil and rock pore size distributions affected by the regularization factor. The second step of partitioning these overlapping peaks for fluid types is usually performed using manual cut-off, Gaussian decomposition, or machine learning methods, with considerable uncertainty and inconsistency. The new inversion method, Anahess, generates a limited number of unique discrete components that directly correspond to fluid types from the raw relaxation data.

The new NFDM workflow, a commonly-used ILT and an improved ILT method are applied to T1T2 measurements on synthetic samples, bulk fluid mixture (oil and water), and shale samples from multiple wells. For the synthetic samples of discrete components, the new method returned the components of accurate amplitudes and T1T2 relaxation times, while the ILT methods only gave approximate results through manual partitioning. The NFDM results from mixed bulk fluids also agreed very well with those from separate measurements. The true potential of the new workflow was illustrated in the analysis of shale samples, where different fluid types such as free oil, free water, absorbed oil, and clay-bound water, were easily determined and quantified by direct assigning the discrete components based on their T1 and T2 values according to a general fluid type NMR scheme. The production of different wells is expected to correlate positively with the free oil saturation. In summary, fluid typing and saturation determination were achieved using the new NFDM workflow with the Anahess inversion method, which eliminates the uncertainty, ambiguity, and inconsistency of existing ILT-based two-step approaches. Further applications to well logging and other NMR measurements using discrete inversion methods, including Anahess, are worth investigating.
Impact of Waxphaltenes on Overall Stability of Asphaltenes, Paraffins, and Emulsion
Authors: Punase Abhishek , Smith Rashod , Burnett Will , Mutch Kevin
Published: October 2023

Recent studies revealed that field deposits collected from production tubing of offshore wells often exhibit compositional variation pointing to more complex fouling process than original predictions based purely on asphaltene or paraffin instability. This deposit mixture generally comprises of 50-60% asphaltenes, 30-35% paraffin and remaining highly polar organics. The objective of this work is to understand the impact of Waxphaltenes co-precipitation on the overall performance efficiency of asphaltene inhibitors, paraffin Inhibitors, and Demulsifiers.

Routine screenings and initial chemical treatments were found unsuccessful for both asphaltene and paraffin application. Firstly, the oil sample was fully characterized though Fourier Transform InfraRed (FTIR) spectroscopy and High Temperature Gas Chromatography (HTGC). A series of dispersion and deposition tests were then conducted in order to identify potential chemistries for treatment. For asphaltene application, dispersion testing was mainly carried out using Asphaltene Differential Aggregation Probe Test (ADAPT) technique, whereas deposition tests were conducted on a customized Asphaltene Dynamic Deposition Loop (ADDL) test.

Crude oil characterization indicated presence of unstable asphaltene fraction within the analyzed crude oil sample. Dispersion efficiency with different asphaltene inhibitors revealed possible co-precipitation issue of other crude oil solubility fractions. Further characterization analyses highlighted heavier paraffinic components to have very high affinity towards the asphaltene clusters and creating waxphaltene precipitation issue. Efficiency of traditional asphaltene inhibitor chemistries were observed to not perform well for waxphaltene deposition. Similarly, paraffin application was tested using optical transmittance method and cold finger deposition setup. Moreover, rheological studies also highlighted issue of highly stable emulsion formation leading to complex fluid flow challenge. Improvement in the chemical treatment program and product development based on the knowledge obtained through this holistic work resulted in superior performing formulations. The deposition test results using the improved inhibitor chemistry was tested on ADDL and showed better performance than the traditional asphaltene inhibitor. Cold finger results also yielded softer deposit with overall lower mass on the fingers. Furthermore, considerable reduction in the emulsion stability was as obtained with addition of the combinatorial product.

The new approach presents a unique opportunity to revisit the way we do product development allowing chemical treatment strategy to be adopted and aligned based on actual deposit characteristics. Findings from this work allows more objective and reliable strategy to be adopted for offshore production with flow assurance management challenges caused by waxphaltenes deposition.