bluuebunny/crossref_metadata_2025 huggingface dataset:
Combining DAS and DTS Measurements for Oil-Water Two-Phase Flow Profiling in Sucker Rod Pump Wells
Authors: Song Jiayi , Sui Weibo , He Jinbao , Li Junwei , Yang Yanming , Guo Huan , Wen Changyun
Published: October 2023

Distributed temperature and acoustic sensing techniques (DTS and DAS) have been widely used in oil and gas wells of higher rates for flow profiling. However, current interpretation models usually cannot be directly applied to sucker rod pump (SRP) wells. Due to the existence of the sucker rod, the contact mode between the optical fiber and wellbore fluids is different from the pumpless wells. Furthermore, high water cut and pump noises also greatly increase the difficulty of DAS data analysis. This paper presented an improved theoretical model and interpretation method for oil-water two-phase profiling in SRP wells and a field case was used for illustration.

The DTS data analysis was mainly based on a well-established numerical wellbore-reservoir coupled flow/thermal model that considers transient temperature behavior during production tests. Considering the different contact modes between optical fiber and wellbore fluids in SRP wells, a segmented function was adopted to describe the variation of heat transfer flux in different well sections. The DAS data were prefiltered to eliminate the pump noises based on the on-site test results. The possibility of determining the volume proportions of the oil and water phase in the mixed fluid through the utilization of the f-k plot was explored. The strength and energy of DAS data were used for preliminary flow profiling. The DAS flow profiles were used as the initial guess and the final interpretation results were inversed by combining DTS and DAS data. Levenberg-Marquardt algorithm was applied for the inverse procedure.

Compared with pumpless wells, the wellbore temperature in the upper section of SRP wells was closer to the formation temperature, which was successfully characterized by this improved thermal model. The water-cut variation has a limited impact on temperature and it might be further obscured by the oscillation of temperature data to some extent. The flow profile calculated from DAS data served as the initial guesses in the DTS inverse modeling part, which greatly reduced the uncertainty of DTS data analysis and computation cost. The presented model and interpretation method have been applied to an SRP well in Liaohe oil field, China. The interpreted flow profiling by combining DTS and DAS data showed consistent results with that measured by production logging tools. Furthermore, the major oil-production zones were identified, and they are interestingly not the major liquid-production zones.

An improved model and interpretation method to interpret the oil and water allocation in SRP wells was presented. The combining DAS and DTS measurements resulted in more accurate interpretation of oil and water allocation than using the DAS alone. In addition, this method may provide guidance for water plugging treatment in commingled wells.
Joint Optimization of Oil Recovery and Carbon Intensity in a Middle-East Oil Field Under Miscible Water Alternating Gas
Authors: Blanchet M. , Bourgeois M. , Guérin S. , Garnier O. , Chehade P. , D’Alessandro S. , Prinet C. , Marmier R. , Barres-Montel V. , Alhosani A. K. , Alhammadi S.
Published: October 2023

This work investigates how the green-house gas (GHG) emissions of a producing oil field can be reduced through adaptation of the reservoir management, i.e. the injection and production guidelines. Indeed, the world’s energy production must be decarbonized as far as possible, and this includes minimization of the emissions associated to the oil and gas extraction itself. An additional decision criterion for oil and gas projects is the hydrocarbon carbon intensity, which is the emissions total divided by the production total, expressed in kgCO2eq/boe. The reservoir management strategies now attempt the joint optimization of all the following dimensions: net present value, short-term production, final recovery, and now oil carbon intensity. In some WAG fields, several controls are available even after the development is finalized: flow rates of both gas and water in each injector, duration of injection of each phase, possible conversion from WAG to water injection. A method has been devised to perform the joint optimization: a reservoir simulator is coupled with a surface model containing GHG emissions equations for compressors, pumps, turbines according to their throughputs. In brown fields, this emissions model can be calibrated on historical profiles and energy consumption per machine, while in green fields, a synthetical model can be built from theoretical operating curves and calibrated a posteriori. In this work, the method was applied on a giant Middle-East carbonate oil field under Miscible WAG injection. Numerous reservoir management scenarios were run, resulting in new production and injection profiles, together with their associated GHG emissions profiles, without the need for time-consuming loops between subsurface and development or exploitation teams. All scenarios were ranked in recovery and carbon intensity simultaneously. For the selected field, it was found that reservoir management actions can be strong levers to reduce the carbon intensity of the produced oil, where required – typically by 10% or more. The most efficient reservoir management actions for GHG reduction were those that reduce the gas injection rate and therefore the associated gas compression requirements. The actions did not impact the short- and mid-term oil production but lead to a reduction of one point of ultimate recovery. Reservoir management decisions must consequently be compromises between ultimate recovery, carbon intensity and net present value. The integrated production and emissions prediction tool proves extremely helpful to identify the relevant reservoir management scenarios, perform informed arbitration or enforce hard-fixed carbon intensity constraints.
Preventing Process Safety Incidents in Upstream & Downstream Oil & Gas Operations by a Systematic Approach to Strengthen Process Safety & Asset Integrity Barriers
Authors: Tayab Muhammad , Suwaidi Hamda Al , Zaabi Hind Al , Kumar Pravin , Shah Vishal , Saif Abdulla
Published: October 2023

By prioritizing process safety and asset integrity, ADNOC has established a strong safety culture and a track record of safe and reliable operations. Its commitment to safety has helped to prevent incidents and protect its personnel, the environment, and its assets. Process safety incidents in the oil and gas industry can have serious consequences, including injury or loss of life, environmental damage, and damage to assets. Such incidents can occur during exploration, production, transportation, and refining of oil and gas. Some common process safety incidents in the oil and gas industry include: Blowouts: Blowouts occur when there is an uncontrolled release of oil or gas from a well. They can be caused by a number of factors, including equipment failure, human error, and natural disasters.Fires and explosions: Fires and explosions can occur due to a variety of reasons, including equipment failure, leaks, and human error. These incidents can cause significant damage to assets, as well as injury or loss of life.Chemical releases: Chemical releases can occur during the handling and processing of hazardous materials, such as hydrocarbons and chemicals used in production processes. These incidents can result in environmental damage, as well as injury or loss of life.Structural failures: Structural failures can occur due to equipment failure, natural disasters, or inadequate maintenance. These incidents can cause damage to equipment and facilities, as well as injury or loss of life.

An analysis of over 50 Process Safety Events (PSE) involving Loss of Primary Containment (LoPC), both from Upstream & Downstream segments of Oil & gas operations was performed. The causes of these events were mapped with elements of process safety and asset integrity framework to identify focus areas.

Preventing process safety incidents in the oil and gas industry requires a comprehensive approach that includes identifying and assessing risks, implementing preventive measures, establishing barriers, monitoring and maintaining barriers, and training personnel. Companies must also comply with relevant regulations and standards, and continuously improve their safety systems and procedures to ensure that risks are minimized and incidents are prevented. The results indicated that deficiencies and inadequacies in risk identification contributed to majority of process safety events.

To prevent process safety incidents, companies like ADNOC must implement a comprehensive process safety management system that focuses more on risk assessments, and safety training. In addition, companies must prioritize asset integrity management to prevent equipment failures and maintenance issues that can lead to process safety incidents.
Energy Efficiency Surveillance Tool (EEST)
Authors: Al Farsi H. I. , Wahaibi A. , Subhi N. , Maqbali A. , Brockman A. , Rumhi J. , Sabri A. , Abri S. , Shuaily I. , Al Hosni H. , Al Harthi A. , Al Araimi M. , Subhi A. , Willcox P. , Balushi A. , Rashdi M. , Riyami A. , Ghammari R.
Published: October 2023

The oil and gas industry, which is the most energy-intensive of all industrial processes, has a huge potential for efficiency improvements. EEST is an engineering tool embedded in Nibras (PDO's Real Time Operation Portal) to:

Highlight ‘Energy Gaps’ (i.e. where energy consumption is higher than target) Enable proactive identification and implementation of opportunities to save energy, cost and emissions.

This project scope is to deploy EEST across PDO (~650 equipment in 20 assets).

EEST provides a lean dashboard to ‘follow the money’ on energy. It aims to continuously reduce energy consumption and GHG emissions through review and adjustment of energy performance against equipment and system-based targets by human interventions. EEST has been linked to the Exception Based Surveillance (EBS) tool and process where alerts are triggered based on energy gaps and sent to the action owner to proactively close the gaps.

EEST has been implemented without any additional hardware or software cost. It is implemented in PDO's real time operation portal, which is used extensively for WRFM surveillance and process monitoring. It uses standard thermodynamic principles behind all energy gap calculations.
Caprock Porosity and Permeability Characterisation for CO2 Storage Seal Integrity Assessment Using Preserved Core and Drill Cuttings
Authors: Sazali Wan Muhammad Luqman , Buckman Jim , Jingsheng Ma , Yong Wen Pin , Busch Andreas
Published: October 2023

Carbon capture and storage (CCS) requires sealing caprocks to ensure the stored CO2 is contained in the reservoir and not leaking towards the surface. Many caprocks are composed of mudrocks, a siliciclastic sedimentary rock with a high clay content. We here analyse such a caprock from the Field S which is a potential CO2 storage site in the Sarawak Basin, East Malaysia. The determination of important caprock properties, like porosity and permeability, is often difficult and requires fresh core material that is adequately stored for lab testing. When such core material is not available, drill cuttings might be used as alternatives to predict formation properties if suitable empirical relationships are available which is the objective of this study. Therefore, we performed a petrophysical characterisation of core and cutting samples using mercury intrusion porosimetry, unsteady state pulse decay permeameter, nuclear magnetic resonance and helium pycnometer measurements. Only MIP and helium pycnometer are suitable to determine porosity and permeability on drill cuttings, while plug samples can be used for permeability tests under subsurface stress conditions. The lab data has then been correlated with well log data to further understand the porosity and permeability trend for prediction purposes. The caprock in Field S is divided into two facies (Seal A and Seal B) with varying clay contents of ~20 and ~40% respectively. However, laboratory derived porosity and permeability values do not vary significantly between the two facies. This might be because Seal B (higher clay content) is significantly over-pressured compared to Seal A, potentially resulting in porosity preservation during compaction, resulting in increased permeability. This is consistent with the time-to-depth conversion from seismic data, where Seal B is identified as being undercompacted in comparison to Seal A. Here, we will present our workflow in predicting porosity and permeability of caprocks based on a petrophysical and mineralogical database developed for Seal A and B. We will discuss issues with this approach and its potential and highlight the difficulties in determining permeability from confined plug or unconfined cutting samples.
The Path to Sustainable Cementing: Embracing a Non-Portland Cement Solution for Oil and Gas Wells
Authors: Abdelaal Ahmed , Elkatatny Salaheldin , Fattah Ahmed Abd El
Published: October 2023

Geopolymer cement shows great promise as an alternative to Ordinary Portland cement (OPC) in the oil and gas industry due to OPC's environmental concerns and high energy consumption during manufacturing. While geopolymer cement is already widely used in the construction sector, its full-scale application in the petroleum industry is yet to be realized. One critical area where geopolymer cement can play a significant role is in high-pressure well cementing applications. To replace heavy-weight Portland cement slurries in these applications, the development of high-density geopolymer cement becomes essential. However, there is a challenge associated with high-density cement slurries that use dense materials as weighting agents. This challenge is known as sedimentation, which leads to issues like heterogeneity and density variation along the cemented sections. Overcoming this problem is crucial for ensuring the effective and reliable use of high-density geopolymer cement in the oil and gas industry. The target of this work is to introduce a new formulation for heavy weight geopolymer systems and evaluate the use of perlite powder as an anti-sedimentation additive in these systems. The study involved the preparation of Hematite-based Class F fly ash (FFA) geopolymer cement slurries with different concentrations of perlite (0%, 1.5%, and 3% by weight of binder (BWOB)). To assess the sedimentation problem, the API method was used. Various geopolymer properties, such as unconfined compressive strength (UCS), elastic properties, and rheological properties, were examined in relation to the effects of perlite. The results indicated that the inclusion of perlite in high-density hematite-based FFA geopolymer led to a significant reduction in the sedimentation issue. This improvement was achieved by increasing the yield point and gel strength of the slurry. Moreover, the UCS showed an increase with increasing the percentage of perlite. The evaluation of young's moduli (YM) and Poisson's ratios (PR) demonstrated that the developed perlite-based geopolymer systems exhibited greater flexibility compared to Class G cement systems. Based on the findings, it was concluded that the optimal perlite concentration for addressing sedimentation while maintaining desirable mixability and rheological properties was 3% BWOB.
Configurable Adaptive Chemical Inflow Control Device Eliminates Intervention
Authors: Asthana P. , Sulaiman A. , Jacob S. , Bukhamseen A.
Published: October 2023

The successful application of Passive and Autonomous Inflow Control Devices (ICDs) to delay water breakthrough, extend well life and increase recovery in Horizontal wells is one of the major technical achievements in the oil and gas industry in recent years. These devices are used as open hole completion equipment to balance inflow along the well borehole section and have enhanced well performance in an efficient and cost-effective manner.

To understand the history and background of the field challenge and previously proposed solutions, the paper presents comprehensive and chronological evolution of ICD's through time. This timeline starts with the introduction of conventional ICDs evolving to adaptive ICDs, and presenting the way forward for the technology. This paper introduces a new Chemistry based Autonomous Inflow Control Device (Chemical-AICD or C-AICD) for oil wells which restricts water based on chemically induced alterations on fluid path. The operation of these devices is completely independent of viscosity and density and need no intervention for water shutoff. The design allows for injection activities even after the device is closed.

The operational of the device incorporates a time trigger selective water/oil dissolvable mechanism on thin coatings applied on a ball. The time and environment dependent selective dissolution changes the diametrical position of the ball within a specially designed funnel, changing the flow port area available for inflow. While newer, advanced completion technology is created to enhance well performance, it is often more complex in design and field installation and comes at a higher cost than existing field-proven technologies. The revolutionary Chemical-AICD design allows applications for oil production in fields where minimization of water production is desirable, while being both cost effective and efficient. A wide range of applications for interventionless water shutoff are presented with a comparison between various ICDs for a typical application to showcase the unique technical and economic benefits of a Chemical-AICD.
Challenges and Lessons Learned: Rotating Packed Bed (RPB) Technology for Acid Gas Removal
Authors: Rahman F. H. , Salihuddin R. S. , Yiin T. K. , Surmi A. , Zuhdi M. F. A.
Published: October 2023

Natural gas produced from many major reservoirs can contain high amounts of carbon dioxide (CO2) and must be treated to meet typical specifications for pipelines or liquefaction plant feed (Hassan et. al 2018). These treatment processes often require high-pressure operations forming highly concentrated CO2-rich streams. There are many factors that can be stumbling block for the development of such a field with high contaminants of CO2.

World high CO2 gas field distribution is shown in Figure 1 (Burgers et al. 2011), some of the fields are stranded due to high CO2 content and not economically attractive to develop due to current oil price. Hydrocarbon resources with high CO2 content from 15 to 80% mol most of the fields are in south-east Asia, northern Africa, Europe, Brazil, Australia and USA, these fields are still undeveloped or under-develop. There is a need for "game changing" technology to overcome this barrier. It is not as simple as developing other green fields, the challenge is more on separation technology and heat integration, to meet project economics. Not only that, CCUS (Carbon Capture Utilization and Storage) is also a challenge whereby the produced CO2 from reservoir needs to be store back to geological storage or to convert it into other useful products (Hassan et. al 2018).
Comprehensive Screening of Available Technologies to Improve Productivity of Complex Undeveloped Carbonate Reservoir for Optimizing Field Development Plan Abu Dhabi UAE
Authors: Sanchez E. , Moreno B. , Dantla V. , Safaa J. , Jamal Haj Bin Naqeh S , Kadeeb M.
Published: October 2023

"M" is an undeveloped thin and tight carbonate reservoir consisting of four porous bodies isolated by the presence of intra-dense layers. The prominent layer is four feet of thickness. Applying conventional acid stimulation in "M" has been ineffective to increase wells productivity and sustainability. Therefore, the objective is to evaluate different technologies to optimize wells design and improve productivity, overcoming the reservoir challenges with cost efficiency for full-field implementation.

It took the outcome of integrated reservoir analysis for helping in the selection of the best technology based on the results and lessons learnt, that had been applied in different development reservoirs, chasing analogy and comparing similarities in rock-fluid properties such as: composition, architecture, porosity, permeability, water saturation, and PVT, from core, logs, and production test analysis. Thus, induced hydrofracking, fishbone, abrasive jetting and limited entry liner were screened for feasibility. Once the technology qualified, the economic analysis and detailed design was established for planning purpose to be implemented in the first horizontal producer in "M" reservoir.

A horizontal well was drilled in a sheet-like carbonate reservoir (pancake stratigraphy) with the advantage of having geosteering technology. It vanquished the structural complexities and the well remained in contact with the reservoir 3500 ft out of 4000 ft in four ft of thickness, nevertheless, two anomalies such as detected shear zones while drilling tried to put the well outside the target. The multidisciplinary team and real time analysis made the well always to come back on target without compromising time efficiency. The well was completed as producer with electrical semisubmersible pump as artificial lift method.

According to the feasibility and screening of the technologies, abrasive jetting resulted in the most effective technique, for production enhancement as cost-effective alternative to induce hydrofracking and other applications in "M" reservoir as a trial. Abrasive Jetting is conducted with 28% HCL, and the distance between stages is designed ~ 20 - 30 ft. to create the channels for maximum production. The expected average wormhole and skin reduction are 1.3 ft and 2.3 respectively. The production testing will be executed to evaluate the well performance, pre and post abrasive jetting job.

Based on the successful application of abrasive jetting technology in the first horizontal producer well in "M" reservoir, the technology will be deployed in the marginal reservoir for full field development plan.
Physics Informed Machine Learning Models for Simulating CO2 Injection into Saline Aquifer
Authors: Sheth S. M. , Shaykhattarov M. , Dias D. , Sathujoda S. T. , Coker O.
Published: October 2023

The injection of carbon dioxide (CO2) into saline aquifers is an important strategy for mitigating greenhouse gas emissions. However, accurately simulating this complex process is computationally expensive, requiring numerical models handling the underlying physics of the system ranging from thermal effects to geochemistry. In recent years, Physics Informed Machine Learning (PIML) models have emerged as promising complimentary tools to physical simulators, leveraging the power of machine learning while incorporating prior knowledge of the physical system.

In this work, we present a PIML model for simulating CO2 injection into saline aquifers. This model is based on an auto-encoder formulation that compresses the state image, that is pressure and saturation distributions and trains a fully connected neural network that can predicts the evolution of the variables in time. The model consists of an encoder that performs the said compression, a transition layer which takes in the well controls and injection rates as inputs, and the decoder that projects the solution from the null space to the original physical space.

The training dataset which includes spatial and temporal data for a limited ensemble of reservoir models with varied well controls is generated using a full fidelity physical simulator which performs reactive-transport calculations and models CO2 injection into a saline aquifer. A deep network is trained using TensorFlow and physical loss functions are augmented along with traditional reconstruction losses. The training of large field models is done using a domain decomposition- based algorithm that breaks up the physical domain into smaller sub-domains and the resulting training is about an order of magnitude faster than traditional full field algorithms. Once the training is performed, the model is deployed on a much larger ensemble with validation of random realizations using the physical simulator.

We present results on a heterogenous three-dimensional subsurface model and highlight the potential benefits of PIML models, including reduced computational costs, improved accuracy, and increased flexibility. The resulting inference workflow is several folds faster than running traditional full fidelity simulators on an ensemble of realizations. Additional results are presented on cases with deformed geometry and complex structural elements such as faults and pinch out cells.
Enhancing Drilling Efficiency in Soft and Plastic Formation: A Field Trial of Hyperbolic Diamond Element (HDE) Bits in Eastern Offshore Basin and Assam-Arakan Basin, India
Authors: Prakash S. , Zayyan M. , Narayanan S. , Haque A. M. , Soi A. , James B. , Menon R. , Sharma V. K. , Nandi D.
Published: October 2023

In the ever-evolving landscape of the oil and gas industry, infill drilling plays a crucial role in maximizing reservoir recovery. It involves drilling additional wells within an existing field to efficiently extract remaining hydrocarbon resources. While infill drilling itself is vital, the speed at which it is conducted becomes equally significant. A larger number of wells drilled in a year will in turn ensure higher production by tapping into the small leftover patches of oil and gas in any mature field. Assam-Arakan Basin, Cambay Basin, and Eastern Offshore Basin are three such similar mature fields in India where the operator drills a huge number of infill wells to meet production targets. Accelerated infill drilling also contributes to improved field development, enhanced reservoir management, and mitigated reservoir risks. The economic viability of infill projects is significantly enhanced by reducing drilling cycle times and achieving cost savings. As the industry strives to unlock the full potential of existing fields, faster infill drilling serves as a key enabler for sustainable and profitable hydrocarbon extraction in an evolving energy landscape.

The Assam-Arakan Basin in northeastern part of India is the oldest oilfield in India and has been in production since 1901. The field reached its plateau of production around 1970–1990 and has been on a declining curve lately. This basin has some unique challenges in terms of lithology being drilled; soft and sticky Girujan clay formation, abrasive Tipam sand, and problematic Kopili formation. While the Tipam sand causes a lot of wear and damage on the PDC bits, pipe sticking challenge is of primary concern in the Kopili formation. Girujan clay formation on the other hand, even after being very soft and easy to drill, causes the bulk of challenges in terms of low penetration rate and multiple trips in the tophole section due to bit balling issue.

The Cambay Basin in western India is also an aging field that has been in production since 1960s and drills a huge number of infill wells each year to meet production targets. The Cambay Basin exhibits a complex geological structure, characterized by faulted and folded formations. These structural complexities pose challenges in wellbore stability and can lead to difficulties in drilling and maintaining wellbore integrity. Lithology wise however the tophole sections do not pose a significant challenge for drill bit design. The major flat time while drilling however comes from the directional requirement of these wells where a single bit cannot drill vertical and build sections.
Carbon Capture, Utilization and Storage (CCUS) in Tight Oil Reservoir
Authors: Weixiang Cui , Chunpeng Wang
Published: October 2023

Low-carbon and green oil development has become the future strategy for numerous oil companies. It is crucial to implement this strategy proactively, focusing on optimizing the industrial and energy structures. The clean and efficient development and utilization of fossil energy represents the most practical approach for energy and chemical companies to achieve green and low-carbon development, while also addressing climate change. In recent years, many oil companies have been committed to a philosophy of ‘developing resources while protecting the environment, and protecting the environment while developing resources,’ with a strong emphasis on environmental preservation. They aim to enhance the quality and efficiency of their operations, fostering new competitive advantages in the realm of green and low-carbon development. As a pivotal industry in the national energy sector, it is imperative to optimize existing oil development technologies to achieve low-carbon and carbon-reducing growth.

CO2 oil recovery technology mainly includes two aspects. Vertical wells adopt CO2 fracturing + huff and puff flooding integrated technology, and horizontal wells adopt water-based fracturing + CO2 flooding technology, which utilizes the efficient penetration of CO2 in the reservoir and the effect of crude oil viscosity reduction, can greatly increase the recovery rate, and at the same time realize large-scale CO2 storage and reduce carbon emissions, which is not only realistic and economical, but also has great social benefits. Carry out technical research on CO2 oil recovery technology, form the key technology of CO2 fracturing-flooding-storage, carry out research on test areas, form a complete integrated technology system, expand the scale application of integrated technology, and become a large-scale low-permeability tight oil reservoir. Develop the main technology for production.

This technology can effectively solve the development problems in low-permeability tight oil reservoirs, and greatly improve the technical problems of tight oil reservoirs that are difficult to develop and rapid production decline. Through the integrated technology of CO2 capture, storage, and CO2 fracturing huff and puff, water Flat well CO2 huff and puff fracturing stimulation. After fracturing, CO2 realizes energy supplement and gas/oil replacement in the formation, and realizes CO2 storage and oil production stimulation.
Machine Learning Advisory System for Mitigating Downhole Vibrations for Horizontal Sections
Authors: Saadeldin Ramy , Alsabaa Ahmed , Gowida Ahmed , Gamal Hany , Elkatatny Salaheldin
Published: October 2023

Horizontal drilling has become a widely adopted technique in the oil and gas industry due to its ability to maximize reservoir contact and increase hydrocarbon recovery. However, one of the major challenges encountered during horizontal drilling operations is downhole vibrations, which can lead to reduced drilling efficiency, equipment failures, and increased costs. To address this issue, a Machine Learning Advisory System (MLAS) can be implemented to monitor, analyze, predict, and guide to mitigate downhole vibrations in horizontal sections. This research explores the concept of MLAS for predicting and mitigating downhole vibrations, highlighting its potential benefits and key components. A Machine Learning (ML) approach, specifically an Artificial Neural Network (ANN), was employed to predict downhole vibrations through drilling horizontal sections. Artificial Neural Network (ANN) model that utilizes surface rig sensor data as inputs to accurately predict axial, lateral, and torsional vibrations during drilling operations. The study utilized a dataset consisting of 5000 measurements specifically collected from horizontal drilling sections. To evaluate the performance of the model, two metrics were employed. The optimized ANN model demonstrated exceptional accuracy, surpassing a correlation coefficient (R) of 0.97, and maintaining an average absolute percentage error below 2.6%. These results highlight the effectiveness of the developed ANN algorithm in accurately forecasting drilling vibrations solely based on surface drilling parameters. The potential to eliminate the need for downhole sensors makes this approach more cost-effective and efficient.
Digitally Transforming EPC Brownfield Project Execution with AWP: Applying the ADKAR Change Management Model for Scalability and Improved Uptake
Authors: Robertson A. , De Vellis L.
Published: October 2023

This paper proposes the use of a recognised change management tool to significantly improve the successful adoption of digital technology and improve the rate of returns in project delivery.

A brief literature review confirms the low levels of digital adoption in the Energy Industry, particularly where the solutions overwhelmingly focus on technology, overlooking the people element. This paper argues that the human element is critical to success and that the adoption of a change management process will unlock easy-to-correct oversights in digital deployment. Importantly, the change management approach proposed by this paper is agnostic; anyone can use it to improve the uptake of any digital transformation regardless of industry, sector or service line.

This paper relies on a substantive case study to add context to the proposed change management approach. This case study revolves around a digital partnership that introduced Advanced Work Packaging (AWP) solutions across 28 brownfield project sites. Brownfield projects in the construction phase are a recognised area of project delivery where low rates of digital adoption prevail, and digital maturity remains stubbornly below benchmarked industries (Deloitte, 2019).

The application of a proven change management tool, coupled with the notoriously challenging business context of brownfield development, provides insights into unblocking hurdles and improving rates of digital adoption for any industry and service. As a direct outcome, through implementing these lessons learned, the reader can expect a greater return on investment from their digital transformation programme.
Case Study & Learnings of the Fastest Well Drilled in Highly Challenging Northern Region of Pakistan
Authors: Parkash Dayal , Khan Shahjahan , Sarfraz Zaman , Sabir Usama
Published: October 2023

Wells drilled in North Pakistan are notorious for extreme tectonic stresses, pore pressure & geological uncertainties which in turn create significant amount of wellbore instability related challenges. All these problems posit extreme drilling challenges and results in significant NPT. Similar challenges were expected for the drilling of X-2 well being drilled by MOL Pakistan in TAL Block. The well was planned to be drilled to 3965m MD in J-shape profile in 147 days. However, during execution due to geological variance the target was revised to 4150m MD, and the profile was changed to S-shaped to further drill newly identified targets within the target tolerances. Despite the change in profile, increased footage and challenges on T&D, Hydraulics and Geo-mechanics front, the well targets were successfully achieved in 89 days with 30% cost savings from the project.

The conundrum for efficient drilling in North Pakistan has been long explored however several short fallings were recorded in past. The Drilling team of MOL Pakistan deployed efficient data analytics, engineering, robust communication, and quick response skills to execute this project. This paper discusses in detail the thought process adopted during planning and execution of the well. The limiters that were posited and how they were managed.
Gas Piping Condition Monitoring Deployment
Authors: Drygin Sergey , Guagnano Pierfrancesco
Published: October 2023

Machinery Diagnostic Services (further referred as MDS) has been invited to evaluate the possibility of monitoring the intensity of induced vibration on the gas piping mounted under a road traffic bridge. In fact, the main scope is to evaluate, via the amplitude level, the risks connected to the structural integrity of the system, strictly connected to the possible condition degradation of the bridge (and in general of the structures where the piping is anchored) which can lead to interruption of the continuity of gas delivery. The objective is obtaining the information regarding the vibrational responses, the natural frequencies, and the related modal shapes, in order to optimize the distribution of permanent sensors which will be form the condition monitoring system to be installed in the immediate future.

It has to be noted that Customer does not own the bridges, but their piping structures are strongly dependent from bridges stabilities.

It has also been highlighted that in 2018, during a rainstorm on 14 August, a 210-metre section of ponte Morandi viaduct collapsed and tragically 43 people died.
Chemical Inhibitors for Asphaltene Control in the Oil Industry: A Comprehensive Review of Laboratory Experimental Techniques and Performance Evaluation
Authors: Ali Syed Muhammad Aun , Zaidi Syeda Fardees , Ali Syed Imran , Louis Clifford , Lalji Shaine Muhammadali , Haneef Javed , Ali Syed Muhammad
Published: October 2023

Chemical inhibitors are essential in addressing asphaltene-related challenges in the petroleum industry. This study evaluates their performance using laboratory experimental techniques and identifies suitable methods for specific functions like inhibition, dispersion, and deposition. Through a systematic literature review, this research analyzes existing laboratory techniques for assessing the effectiveness of chemical additives in managing asphaltene precipitation and deposition. The findings highlight the significance of chemical inhibitors in preventing production losses due to deposit blockages in fields. The study also examines the governing factors that impact their performance, such as additive dosage level, operating conditions, and operating medium. This research provides a comprehensive evaluation of laboratory experimental techniques, enhancing the understanding of chemical inhibitors’ mechanisms. It offers valuable insights for operating companies and service providers to select appropriate techniques for screening and selecting chemical inhibitors. The asphaltene control process through effective chemical treatment by the petroleum industry can improve operational efficiency and ensure sustainable hydrocarbon recovery from oil fields.
A Journey of FWI Offshore Abu-Dhabi – From Concept to Reality
Authors: Varghese Anish , Paul Subhrankar , Domont Sonia , Damianus Fritz , Mccarthy David , Mahgoub Mohamed , Cambois Guillaume
Published: October 2023

Commencing in 2018, ADNOC undertook a mega seismic campaign (Cambois et al., 2019), acquiring approximately 30,000km2 of ocean bottom sensor (OBS) data in the challenging imaging environment of offshore Abu Dhabi. The region posed difficulties due to ultra-shallow water depths, a hard water bottom, and a complex near surface. To accurately image deeper reservoirs, a precise velocity model of the complex near surface was crucial. This study discusses how FWI was utilized to overcome these challenges and its impact on velocity model building and imaging.

Although FWI is a standard technique in many geological basins, its application in the offshore Abu Dhabi region proved to be challenging. The presence of a hard water bottom resulted in strong elastic effects, while the near surface exhibited significant velocity variations and high anisotropy (with epsilon parameter > 30%). Nonetheless, Hermant et al. (2022) recently achieved successful application of FWI in the offshore Abu Dhabi region. The key to their success lay in careful data selection, conditioning, and the choice of an appropriate initial model. Data was meticulously chosen to avoid interference from mud-roll and guided wave energy, and pre-conditioning was kept to a minimum. Given the high apparent anisotropy in the near surface, the selection of a good initial model was critical. Well data and Backus averaging (Backus, 1962) were utilized to generate initial velocity and anisotropy models. Diving wave updates were limited to the very near surface, while reflection data was employed to extend the model updates and incorporate higher frequency details.

Encouraged by the promising initial results, diving wave FWI was subsequently applied to a 14,000km2 area of offshore Abu Dhabi as part of an ongoing depth velocity model building process. The inclusion of the FWI model for the near surface led to a significant enhancement in the final depth velocity model and the resulting migrated image. FWI utilizing reflection data exhibited notable improvements in capturing fine details, such as karst features, within the velocity model. Consequently, FWI with reflection data was implemented in two other surveys to generate high-resolution velocity models, thereby improving structural imaging, and identifying deeper faults.

In summary, this study demonstrates that diving wave FWI successfully produced a near surface velocity model over 14,000km2, leading to substantial improvements in imaging and facilitating the delineation of deeper structures. The incorporation of high-frequency updates, including reflections, enhanced the resolution of the existing model and the interpretation of geological structures, such as faults. These findings underscore the transformative potential of FWI in velocity model building within the offshore Abu Dhabi region.
The Importance of Utilizing Organizational Culture in Achieving Organizational Excellence Models
Authors: EL-Makarem Asmaa Abou
Published: October 2023

Objective

The aim of this paper is to investigate the impact of Organizational Culture (OC) on achieving Organizational Excellence (OE) in the Petroleum Industry, through defining the different types of Cultures embedded in any organization- utilizing Denison Model four key cultural traits (Mission, Consistency, Adaptability, and Involvement) and measuring Organizational Excellence dimensions (Customer focus, innovation, and people commitment).

Method, Procedures, Process

A Quantitative method was chosen, with a deductive approach and positivist hypotheses, the data were collected and analyzed using the descriptive approach to test the hypotheses.

Data were collected through a survey questionnaire of (17) statements, divided into two parts; Part one: to measure the dependent variable, the OE dimensions (Customer focus, innovation, and people commitment). Part two: to measure the independent variable the OC.

The target population were the employees of the Petroleum industry. The sample used was a convenient sample of 384 employees from different Petroleum companies in Egypt. The sample included employees from managerial and non-managerial levels.

Results

The study revealed that OC-OE have a strong positive linear relationship at the level of significance 1%., which shows that OC embedded in the studied organizations has an effective role in achieving OE. In addition, the impact of OC on OE varied from one OE dimensions to another. The strongest relationship was between the OC and the OE -Innovation, then people commitment, followed by customer focus at the level of significance 1%.

Also, the paper showed how the excellence starts by excellence employees, and that OC embedded in any organization can vary from one culture trait to another, and that having a balanced culture, as well as advantaging the OE and its dimensions, will help organizations to achieve the quality excellence model program. However, having the proper culture can become a challenge to decision makers, to alter company plans, strategies, involvement of employees, adaptability, investing in innovative ideas, engage and empowering employees and enhance the customer focus strategies and consistency to cope with the regular changes in the environment; and to fit with the excellence programs to gain the benefits of excellence not only in quality but also in their market share, sales, profits, employ morale and competitiveness.

This model can be applied by various companies in many countries to assess the types of cultures in each organization, and the importance of setting a remedial plan to implement the excellence models, to be measured as a longitudinal approach to capture the changes over time in employee excellence, and level of excellence and sustainability reached.
4D-Coprocessing: Case Study Offshore Abu Dhabi
Authors: Kirstetter O. , Mahgoub M. , Cambois G. , Papillon F. , Varghese A. , Six2 B. , Reboul R.
Published: October 2023

Time-lapse seismic monitoring is challenging for carbonate reservoirs because of the stiffness of the rocks and the low sensitivity of their elastic properties to reservoir changes over the time-lapse of the 4D seismic. This explains why there are so few examples in the literature of successful seismic time-lapse surveys in carbonates in the Middle East. This paper presents a case study of time-lapse seismic offshore Abu Dhabi, focusing on the seismic processing part of the workflow. As the repeat acquisition survey was not designed for 4D purposes, we relied on processing to minimize the non-repeatability effects. Our methodology consisted of applying a special seismic co-processing sequence between the base and the monitor surveys with a dedicated 4D workflow, starting after Up/Down deconvolution. A rock physics model was also derived to assess and quantify the expected changes with production (in this case water injection). The Likelihood of 4D signal detectability was achieved even though seismic acquisition repeatability was very low. 4D metrics were overall improved throughout the processing despite the high non-repeatability of the two acquisitions and the independent 3D pre-processing sequences applied to both vintages. The 4D Least-squares Kirchhoff migration flow was a particularly relevant step to improve the 4D metrics. As a result of this study, we have defined best practices for 4D seismic co-processing and designed 4D metric attributes such as RMS, NRMS and predictability to assess the improvement of the seismic acquisition repeatability through 4D seismic co-processing supported by a rock-physics based petroelastic modeling.
AIML Provides the Efficiency and Precision in our Subsurface Geological Understanding
Authors: Sajid Muhammad , Rajput Seemant , Ghazali Ahmad Riza
Published: October 2023

We created a seismic feature recognition system based on Artificial Intelligence Machine learning (AIML) and evaluated its effectiveness and precision in comparison to conventional seismic interpretation methods. Findings indicate that performance is influenced by both the generalization of seismic features and the quality of the input data sets. Machines are more effective than conventional methods at identifying seismic characteristics, but they require transfer learning to keep up with new seismic features, necessitating the multi-model strategy covered in this study.