bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantitative Assessment of CO2 Mineral Trapping Capacity in Presence of Sealing Fault in Carbonate Sequences: A Numerical Approach
Authors: Fathy Ahmed , Arif Muhammad , Adila Ahmed Sami , Raza Arshad , Mahmoud Mohamed
Published: March 2023

Mineral trapping is believed to be the safest and the most secure CO2 sequestration technique where the injected CO2 could be mineralized in the long-term (exceeding 102 - 103 years) geologically within subsurface formations. Nevertheless, the high complexity associated with CO2 mineral trapping capacity predications obscures the in-depth understanding of CO2 mineralization. In this study, a numerical simulation is adopted to demonstrate the impact of carbonate mineralogy in presence of a sealing fault on CO2 mineral trapping capacity.

Field-scale CO2 pilot topographic model for three distinct carbonate minerals is simulated to depict the mineral trapping capacity. Thus, realistic petrophysical parameters, reservoir characteristic curves, and other in-situ conditions are upscaled to mimic carbonate formations. Thereafter, the amount of CO2 mineralized is estimated for compositionally distinct reservoirs. Additionally, the effect of injection pressure on CO2 mineralization is assessed upon precipitation/dissolution kinetics calculations. Moreover, the effects of well placement and perforation depth on mineral trapping potential of calcite, dolomite, and siderite dominant reservoirs are assessed.

The mineral trapping capacities computed show that increasing injection pressure (base injection pressure to 1.5*base injection pressure) monotonically increased the mineral trapping capacities for calcite and dolomite. However, siderite seems slightly insensitive to the injection pressure increase. This monotonic trend is attributed to enhanced radial displacement and restricted plume migration upward as the injection pressure increases. Moreover, proper CO2 injector placement showed significant enhancement in mineral trapping capacity especially if the injector is near to the fault plane on the leaking side. This study provides in-depth theoretical understanding of the mineralogy effect on CO2 mineralization potential in faulty carbonate sequences. This is driven by the insignificance interest mineral trapping has gained over the years compared to other trapping mechanisms. This is because of the extremely long storage duration needed for mineral trapping to reach its maximum potential. Importantly, the results suggest that CO2 mineralization within carbonate reservoirs immobilize CO2 – thus assisting in stable and long-term permanent storage.
Advanced Lower Completion Technology Applications in Miscible Gas Injection EOR - Unlock Value for Multi Reservoir Onshore Fields
Authors: Xu Siqing , Baslaib Mohamed , BinAmro Ahmed
Published: March 2023

Miscible CO2 flood – similar to miscible hydrocarbon gas injection - is a well-established proven EOR development scheme. There have been a large number of CO2 EOR developments worldwide, with deployment in both carbonate and clastic reservoirs. Potential controlling factors on CO2 EOR incremental production and recovery are well understood and widely published. This paper presents an integrated CO2 EOR development study, with emphasis on advanced technologies application – the deployment of advanced lower completion technologies. This paper is a follow up companion paper, presenting additional results, to a previous paper by Xu S. et al (2021). A review is provided concerning successful application of advanced lower completion technologies: namely Maximum Contact Reservoir (MRC) wells, Limited Entry Liner (LEL), and Fishbone drilling. The reservoir geological characteristics from three Onshore Abu Dhabi carbonate reservoirs are presented, and key factors which may lead to poor reservoir sweep are identified. Fine scale 3D compositional models were developed, to simulate reservoir performances when advanced lower completion technologies are deployed. The results show significant injection/production performances compared to conventional horizontal wells development schemes. When under CO2 EOR development, the major recovery mechanisms leading to sweep improvements are highlighted. The deployment of such lower completion technology may prove to be a valuable enabler in a future CO2 EOR development scheme.
ESP Failure Prediction in Water Supply Wells Using Unsupervised Learning
Authors: Reddicharla Nagaraju , Sultan Ali Mayada Ali , Alshehhi Shamma Saeed , Elmansour Ayman , Vanam Prabhaker Reddy
Published: March 2023

Water injection is seen as one of the key field development strategies to achieve the mandated production target as it will maintain reservoir pressure as well as improve sweep efficiency and increase field recovery factor. In current practices water supply wells workovers are planned after Electrical Submersible Pumps (ESP) are failed by adopting run to fail approach. This lead to decrease in well availability and increase in down time which impacts water injection cluster capacity in giant matured onshore oil field.

The objective of this solution is to early detect the failures for ESP wells using Machine Learning (ML), by demonstrating the feasibility of this approach and verifying that the concept has practical potential, the tool can be used to reduce deferment and increase well availability either by extending time-to-failure or better planning and scheduling the workovers. In this solution, Predictive Analytics model was developed based on Algorithms using field sensor data, and well failure history to predict ESP well failure probability. Due to the limited available ESP real time data, it would be a challenge to have an accurate model. The downhole and temperature data is not available in these ESP wells. Hence, we have adopted unsupervised classification approach combined with statistical calculations such as MTBF based on failure history. The solution provides a probability of ESP failures based on the anomalies (anomaly severity) detected from unsupervised machine learning model (individual cluster based), MTBF & number of starts. The probability is normalized based weight-based approach. Additional criteria can be added and considered in the future to fine tune the model and predictions.

The approach has successfully evaluated on 34 water injection clusters in this giant field. The model is able to predict 77% of failures historical failures successfully. The limitations in ESP down-hole data availability and real time quality issues impacted model accuracy. The solution has been successfully deployed in real time mode and able to predict failures 90 to 120 days before failures. This has resulted increase in well availability by 10% and increased water injection system capacity.

This machine learning based approach has been extended to all water injection clusters and also capitalized in other fields to increase well availability and grow capacity with the increasing demand for water injection to sustain and grow production volumes
Geochemical Interactions Among Rock/CO2/Brine Systems: Implications for CO2 Geo-Storage
Authors: Adila Ahmed Sami , Raza Arshad , Zhang Yihuai , Mahmoud Mohamed , Arif Muhammad
Published: March 2023

Carbon Capture and Storage (CCS) is one of the promising techniques to mitigate carbon dioxide emissions and move towards net zero targets. The efficiency of a geological storage process is, however, a complex function of CO2/rock/brine interactions. In particular, the effect of geochemical interactions among CO2/rock/brine systems in an aquifer and its associated impact on wetting behavior has not been rigorously investigated before.

In this work, we study the effect of the critical parameters affecting the CO2/rock/brine system wettability from a geochemical perspective. In particular, we study the effect of temperature, pressure, and salinity on the wettability of the CO2/calcite/brine system. The wettability was assessed based on the disjoining pressure, which was calculated from calcite surface potential. The geochemical simulator used is based on surface complexation modeling and takes dissolution and precipitations reactions of the minerals and aqueous species into account.

The results show that increasing pressure decreases the concentration of calcite surface species >CaOH2+ and >CO3−, while it increases the calcite surface species >CaCO3−. However, increasing temperature increases the concentration of calcite surface species >CaCO3− and >CO3−, while it slightly decreases the calcite surface species >CaOH2+. The results also show higher calcite surface potential and disjoining pressure at higher temperatures and lower salinity, which reflects an increase in water wettability (or a decrease in CO2-wetness) and greater CO2 storage potential in calcite-rich aquifers at these conditions.

This paper provides insight into the effect of different influencing parameters on the CO2/rock/brine interactions and CO2/rock/brine wettability, which can help understand the geochemical processes involved in CCS projects under a wide range of operating conditions.
Essential Ingredients of Effective Project Management: A Case Study of Project Execution in the South Pars Mega-Projects
Authors: Daneshkhah Vahid , Younesi Gholamreza , Karbalaee Akbari Meisam , Daneshkhah Hamed
Published: March 2023

During the past decades hundreds of wells have been constructed in the giant South Pars gas field with different approaches and methodologies leading to diverse outcomes and results. Interestingly enough there have been many operators in the field with distinct performances yet by deploying the same vendors and service providers held in common. By considering that it is statistically proven that the larger the project budget, there are higher chances for failure, effective tailoring of methodologies in large scale mega-projects would be crucial and decisive. In many cases failures are a consequence of simply applying methodologies already experienced in small scale projects on complex and sophisticated projects with a variety of influential factors and a huge network of stakeholders. The study has provided an insight on how effective approaches in project management or conversely mismanagement could play as the main rout cause in a chain of events corresponding to either saved time or Non-Productive Times in well construction operations by presenting real cases elaborated in detail.

Cases show how failure in collecting requirements and recognizing the interdependencies among each necessity in the early stages of the project and subsequently overlooking the related cost, time and risks could cause massive cumulative financial loss. Additionally, failure to recognize wise investments in vendors and service providers as the 1-10-100 rule which explains how failure to take notice of one initial investment escalates the financial loss exponentially would have staggering consequences. The current paper explains how being proactive in an extensive planning phase could ease the execution stage as a great investment in time spent. From a human resource perspective, it has been demonstrated that how the ability and skills of the project team e.g. effective communication in complex networks with multiple reporting relationships and data-driven decisions by statistics could prevent cognitive biases and errors in decision making. Furthermore, powerful alignments come from shared and common motivations and morale for all engaged parties and the supply chain being service providers, rig contractors or the field operator and there should be an answer to the question, what's in it for me when asked by each of these parties.

Overall the study presents real cases and lessons learned showing how the main rout causes of Non-Productive Times could go back deeply to ineffective project approaches from a project management perspective in a system dynamic chain of events rather than to just address the emerged symptoms of failure in drilling operation.
In Situ Hydrogen Generation Within Gas Reservoirs
Authors: Afanasev Pavel , Popov Evgeny , Cheremisin Alexey , Mikitin Evgeny , Darishchev Viktor
Published: March 2023

Nowadays, hydrogen is often considered as one of the prospective clean energy carriers. At the same time, the traditional hydrogen production methods also produce significant amounts of greenhouse gases or too expensive to be industrial scaled. In situ hydrogen generation in hydrocarbon-containing reservoirs can be one of the promising ways for low-carbon hydrogen production. However, the conversion of hydrocarbons into hydrogen under the hydrocarbon reservoirs conditions has practically not been studied.

This work reports experimental results on the catalytic in situ hydrogen generation from methane under the conditions that can be achieved due to the thermal influence on gas-bearing layers. Hydrogen can be generated within gas reservoirs with non-zero residual oil saturation or in the fields with underlying oil-saturated layers due to the catalytic treatment of the reservoir followed by steam injection and/or in situ combustion. First, the thermodynamic restrictions for the process were determined. Then verification concept experiments were performed in the autoclave setup in static and dynamic modes with various operational parameters. The effects of temperature, pressure, and core model type on the hydrogen generation were investigated.

Results show that temperature higher than 550 ºC should be achieved in the active zone of the target reservoir to convert significant amount of methane to hydrogen. The lower temperatures reached at the active zone are inefficient for the hydrogen generation. This effect can be explained by the thermodynamic restrictions and negative influence of the original core on catalyst activity. Nevertheless, hydrogen concentrations up to 70.8% mol. and 34.0% mol. were achieved in the experiments at 800 ºC in the presence of the inert (crushed alumina) and the original core models, respectively. At this temperature, strong reducing conditions influence the catalyst activity. Conducted experiments proved the main principles of the in situ hydrogen generation technology and evidenced that hydrogen generation in gas reservoirs is prospective when realized jointly with the catalyst treatment and in situ combustion method. This innovative technology can help humanity decarbonize the energy sector using unclaimed hydrocarbon resources of depleted and abandoned gas reservoirs without greenhouse gas emissions.
Wettability Characterization of Carbonate Rocks Using a Micro-Scale Approach
Authors: Aboushanab Mahmoud Sami , Al Naimi Khaloud , Al Kobaisi Mohammed , Rahman Md Motiur , Arif Muhammad , Mahmoud Mohamed
Published: March 2023

Wettability is an important factor that influences relative permeabilities and capillary pressure, which in turn impacts the hydrocarbon recovery. Wettability of carbonate surfaces is typically challenging due to their diverse wetting behavior. Wettability has been conventionally quantified using the macro-scale contact angle observations. However, macro contact angle suffers in terms of precise identification of the three-phase contact line. In this study, a new micro-scale approach is presented to determine rock surface wettability. Here we used five different Middle Eastern carbonate samples with different mineralogy. The micro-scale contact angles are evaluated via Environmental Scanning Electron Microscopy (ESEM) using condensation-evaporation approach while the classical sessile drop method is used to determine the macro-contact angles. The results show a notable difference between macro and micro contact angles which suggests wettability variation at different scale of measurement. Depending on micro contact angles, mixed-wet state for all samples is observed, as some samples experienced water-wet behaviour at most of the measured locations, while they showed intermediate-wet behaviour at a few locations. However, based on macro contact angles, only one wetting behaviour is recognized. Therefore, a thorough wettability characterization would require insights at the micro-scale to capture variations in wetting behavior.
Seismic Reprocessing Leads to New Breakthroughs——A Successful Case in the ASH Field, A.G. Basin in Egypt
Authors: Elokr Mohamed , Lotfy Ahmed , Xing Wei , Li Huijing , El Bassioni Ahmed , Moatasem Nader
Published: March 2023

ASH oil field located in the east of the AG Basin in Egypt. Lower Cretaceous Alam El Bueib is the main oil producing formation. Due high heterogeneity of the Abu Roash Members succession in addition to the influence of thick limestone of the Upper Cretaceous and the influence of multiple complex faults, the quality of seismic data is very poor. This is mainly manifested in, a, the variation of vertical velocity in lithology changes resulting a significant error in depth migration; b, the fault imaging is not clear due to low S/N ratio, which leads to serious challenge for structure mapping. Therefore, the seismic re-processing was carried out.

Two key techniques were carried out to achieve the target, that: uses new well VSP data to adjust the velocity model and CRAM PSDM for re-processing.

Adjusting the velocity model: The previous PSDM acquired in 2015 had no well control covering the deeper target of Alam El Bueib Formation but the advantage of using VSP data of ASH-3 well as a well control for building new velocity model of the reprocessed data. CRAM PSDM re-processing: The CRAM (Common Reflection Angle Migration) is a cluster-based imaging system that generates conventional reflection angle gathers without azimuth dependency. Optimal local tapered beams are internally created and imaged to form high-quality image gathers, which can then be used in standard interpretation systems for accurate velocity model building and amplitude inversion (AVA).

Applying CRAM technology in depth migration instead of Kirchhoff depth migration, has a great impact on enhance the final seismic image. The CRAM algorithm is using the Ray path migration of the seismic signal instead of using migration aperture as in Kirchhoff. Applying the ray path migration helps in adopting the seismic trace position ultimately enhance the fault definition and S/N ratio at the deeper target levels.

As a practical case from the comparable seismic sections, same arbitrary line in different seismic volumes, the reprocessed data showed a high level of improvement in fault definition specially in the north portion of ASH field closer to the major fault which was very poor in the previous data. In the reprocessed CRAM PSDM data, the good amplitude extended towards the north and west portions of the field, which allowed to define the faults through Alam El Bueib horizon and decrease the uncertainty of the new proposed well location in the entire field. (Figure 1)

Figure 1 Amplitude comparison between reprocessed and original data, ASH field
Cloud-Based Software for Automated Well Planning
Authors: Hassan Mohamed Ali , Strand Jim , Remmen Per Inge
Published: March 2023

The Automatic Well Design workflow presented in this paper is a starting step to achieve Well Construction Autonomy. This workflow made possible through modern "API" based drilling calculation engines hosted on a cloud computing environment.

In the Drilling Digitalization Infrastructure, everything will be connected via Open APIs, and Real time Machine-to- Machine Communication. Modern Cloud-Based Applications will enable Engineers, within seconds, to automatically execute complex drilling simulations and calculations

This software tool, named WellDesign, is a cloud based single page application utilizing networks and cloud computers for data storage and collaboration. It offers a set of application programming interfaces (API), enabling machine-to-machine communication & 100% automation, where whole or parts of the software can be operated by other computers. On top of this interface, the software tool has a 2D and 3D human graphical user interface, utilizing web technologies such as accelerated 2D (Canvas, 3D.js) and 3D (WebGL, three.js) graphics. This software tool aims to run on all kinds of computers (Windows, Macs) and other interactive devices supporting modern web browsers (tablets, phones and similar).

Well Construction Automation is gradually becoming more prominent in oil & gas industry. It encompasses the application of digital technology in all aspects of well drilling and completion (i.e., automatic well design, digitalization of downhole tools & surface equipment, remote monitoring, real time data transmission, and robotic rig systems).

In today's Industry 4.0 transformation world, easy-to-use cloud-based software can partially automate Oil & Gas wells design. Future software development should be made to produce fully autonomous Oil & Gas well designs while maintaining industry safety & well integrity standards

The Automatic Well Design workflow presented in this paper is a starting step to achieve Well Construction Autonomy. This workflow made possible through modern "API" based drilling calculation engines hosted on a cloud computing environment. In the Drilling Digitalization Infrastructure, everything will be connected via Open APIs, and Real time Machine-to- Machine Communication.

Modern Cloud-Based Applications will enable Engineers, within seconds, to automatically execute complex drilling simulations and calculations

Two automatic design workflows shall be illustrated in detail:

Automatic Well Trajectories Automatic Casing Design
Developing Local Talent from the Concession Area at United Energy Pakistan
Authors: Nizamani Abdul Bari
Published: March 2023

Objective/Scope: The purpose of this paper is to study how UEP has implemented Field Production and Maintenance Trainee Programs. It will further evaluate the effectiveness of the program and how it has benefited the local community and the company.

Methods, Procedures, Process: UEP's Field Trainee program provides opportunities for young people from the concession in which UEP operates. It creates jobs for local youth to get trained and work in the oil and gas sector.

The process to recruit the local and train them is extremely rigorous. The applications are invited via placing an advertisement in the local newspapers. Candidates meeting the criteria, undergo a rigorous test and interview process. Candidates shortlisted on merit are selected. The training of selected local high school graduates is initially performed in the classroom by senior faculty of renowned local Sindh university. After completing classroom training, they embark on an on-the-job training plan under the supervision of seasoned industry professionals.

Results, Observations, Conclusion: Over many decades the UEP trainee program has developed skillset of the locals and has given them employment opportunity. It has provided a talent pipeline for the organization and helped UEP give back to the community as part of its commitment. Several senior positions at UEP are occupied by employees inducted through this program. Some of them are working for other multinational organizations in Pakistan and abroad. Apart from developing the talent pool, this program has increased organization's brand value especially amongst the locals and has helped the organization forge meaningful relationship with the local community.

Novel/Additive Information: This program has been a great success story for UEP. It shows that benefits are not limited to meeting the workforce requirement. Other organizations in Pakistan and abroad can learn from UEP's success and may introduce similar programs. This program is mainly focused on hiring resources for Operations functions. Going forward, the need for introducing similar program for other functions can be evaluated.
Late Time Response Analysis in Pressure Build Up Tests: Challenges and Solutions
Authors: Motaei Eghbal , Ali Anwar Husen Akbar , Rozali M Irsyad B
Published: March 2023

One of the most important features that impacts the facility size and production rate commitment is the minimum connected volume which can be explored through pressure Build Up and any misinterpretation, costs the operators significantly. This paper aims to address the challenges in Late Time Response analysis of pressure Build up well tests that exploits the reservoir boundary. Knowing that the well test response at late time shows the fingerprint of multiple features such as aquifer, sand discontinuity, baffles, faults, boundaries, etc., it will be challenging to quantify the extends of the reservoir using convolved late response.

Two main numerical models were built for oil and gas reservoirs in an elongated reservoir to study the lateral boundary features such as closed boundary and aquifer and understand the effect of these features on late time response to get a clearer response. Using two models, the impact of mobility contrast between the hydrocarbon, boundary distance, aquifer strength, boundary movement and structure complexity was simulated.

The major finding of this paper is that a unit slope straight line can be seen in buildup test which doesn't fit any classical and analytical model for pressure build up as the expectation is to have negative slope and down-ward hump for build up response of closed boundary and aquifer. However, this can be explained through mobility reduction from hydrocarbon (oil/gas) to water. The simulation time (build up test duration) was extended to see the long-term impact theoretically and at the end the same expectation was confirmed by simulation. After radial flow, channel flow (half slope) and then unit slope (mobility reduction) and then at last the drop in the derivative response is observed. However, the drop as signature of aquifer or limited volume happened beyond practical test duration (> 1000 hours).

The work highlights the true workflow to identify the true response from reservoir and have reliable reservoir characterization and shows the case studies that address the cost on 1) misinterpretation of late time response and 2) excluding the well test from analysis due to its complexity to highlight the value and criticality of the integrated analysis.
Investigation of Hydraulic Fracturing Sensitivity to Water Injection Volumes In Wolfcamp Formation
Authors: Saeed Yousef Tareq , Alhajeri Mubarak Muhammad , Barati Ghahfarokhi Reza
Published: March 2023

Hydraulic fracturing is a common stimulation technique in oil and gas production to stimulate wells with low permeability. An optimum fracture half-length is designed by injecting the right amount of fracturing fluid to achieve successful results. Otherwise, injecting lower than the optimal amount will cause a poor fracture network, water blockage, and phase trapping of oil and gas behind the fracture space while over injection may result in frac hits and unfavorable economics. This paper presents the importance of the optimum fracture half-length and the role of injection volumes to generate such a length. CMG models were created to study the correlation of different parameters during hydraulic fracturing in the Wolfcamp formation (Permian basin): fracture permeability, water saturation, and capillary pressure. Three CMG models with different fracture half-lengths of 100ft, 200ft, and 350 ft were created. Sensitivity analysis of facture permeability was performed on each model using different values, e.g. 0.1, 1, 10, and 100 md. Representative cases were selected based on the sensitivity analysis results on fracture permeability. Fracture permeability was then changed in each model and was 5 md for the first model, 10 md, and 20 md for the second and third models, respectively. The effect of water saturation was also studied by changing the water saturation from 45% to 55% in an increment of 5% in each simulated model. Finally, the capillary pressure data was added to each model to study the effect of water blockage. Economic analysis was studied to determine the best-case scenario in terms of higher NPVs and RORs. Sensitivity analysis of facture permeability indicated that as fracture permeability increases, then an increase in hydrocarbon production is achieved in which the water saturation was the conclusive parameter. For instance, hydrocarbon production rates were the lowest in the first model which had the lowest fracture half-length and, therefore; fewer water volumes were injected. The second model with a fracture half-length of 200ft as the optimum length provided the optimal amount of injected water and gave the highest amount of incremental Hydrocarbon production, i.e. water saturation and fracture permeability were higher than the previous one. The last model, which has the highest fracture half-length and also the highest amount of injected water showed a significant amount of formation damage. A higher amount of injected fluids caused a high capillary pressure that was responsible for blocking the fractures and caused a decrease in relative permeabilities. The amount of injected water during hydraulic fracturing will significantly affect oil and gas production. CMG models, decline curve analysis, and economic studies showed that designing the optimum amount of injection volumes is key to a successful hydraulic fracturing treatment and minimizing the risk of causing any damage to the formation.
Physical and Numerical Simulations of Offset Well Pair Combined Steam Drive and Gravity Drainage Process to Develop Super-Heavy Oil or Oil Sands Project
Authors: Liang Guangyue , Xie Qian , Liu Yang , Liu Shangqi , Xia Zhaohui , Bao Yu , Zhou Jiuning
Published: March 2023

Steam assisted gravity drainage (SAGD) using parallel dual-horizontal wells made great success in developing heavy oil or oil sands projects. However, the performance may be greatly impaired when shale laminae with high frequency exist. In order to enhance oil production and decrease steam to oil ratio (SOR), this paper conducts feasibility study of offset well pair using steam drive and gravity drainage to develop oil sands project by overcoming shale laminae.

Physical simulations of offset well pairs under three horizontal distance were first carried out to analyze the mechanism. On the basis, homogeneous model and heterogeneous model incorporating staggered shale laminae were constructed, respectively. Then numerical simulations of conventional SAGD well pair and offset well pair using steam drive and gravity drainage were conducted to evaluate the influence of pay thickness and possibility of mitigating adverse impact of shale laminae. Moreover, several configurations of offset well pairs and their application results were proposed.

The results of physical simulations indicate that there is larger lateral steam chamber development compared with conventional well pair. While for numerical simulations, for homogeneous case, compared with conventional well pair, offset well pair achieves similar performance but delaying oil production for 0.5 year, and the performance cannot be improved significantly even if aggressive pressure difference or subcool control is enforced. But for heterogeneous model with existing inter-well shale laminae, offset well pair can significantly improve early to mid-term performance and accelerate early steam chamber growth by enforcing pressure difference. But once steam chamber has grown to a certain height, there is no big difference between offset and conventional well pairs. Furthermore, three configurations of offset well pairs are evaluated including the injector drilled 3 m high and 4 m laterally from the producer, offset horizontal injector and multilateral producer, and multi-stage hydraulic fracturing or dilation assisted enlarge well spacing of 10-30m. Encouragingly, offset horizontal injector and multilateral producer has made great success by a combination of steam drive and gravity drainage in Canadian Surmont oil sands project.

The proposed technology was first studied by combined physical and numerical simulations, and it can be effectively applied to relatively low quality oil sands projects such as thin pay and challenging pay with staggered shale laminae. Several configurations of offset well pairs have been listed as pilot suggestions.
A Novel Technique for the Quantitative Determination of Wettability of a Severely Heterogeneous Tight Carbonate Reservoir
Authors: Al-Sayegh Saleh , Flori Ralph , Al-Bazzaz Waleed , Abbas Abdulaziz , Qubian Ali , Al-Saedi Hasan
Published: March 2023

The objective of this study is to accurately measure the wettability contact angle of a cretaceous carbonate reservoir in a vertical well set-up known for as an unconventional tight carbonate oil reservoir. Also, to investigate the relative heterogeneity of these samples using digitally captured images; these images accurately capture natural pore-system in this carbonate rock samples and their wettability performance attributed towards building a vertical depth wettability/ heterogeneity model. To capture, measure and model natural tight matrix static contact angle wettability in order to understand their new physics that will advance unconventional tight oil reservoir characterization.

Entire vertical well depth reservoir core rock samples, in the form of rock fragments, are selected, then imaged, and then characterized for porosity, permeability, tortuosity/ heterogeneity, and pore/ grain-wettability contact angle in 2D format utilizing SEM-BSE imaging techniques. The generated big data images will be quantified using pre-defined logic for tortuosity/ heterogeneity and wettability contact angle measurement. Each rock sample will process several images captured at X40 (mm), X400 (μm), and X4000 (nm) magnifications and will investigate wettability/ heterogeneity relationships for unconventional tight pore system from the entire vertical depth.

From measured data and computed logics, the major portions of captured rock investigated show water wet tendency. The wettability distribution in the vertical 250 feet shows strong to medium and even weak water-wet system variation (θ = 10° - θ = 90°). The dominant wettability is medium-water-wet (θ = 30° - θ = 60°), and it is found in the middle section of the vertical column. Medium-water-wet indicates a good candidate for secondary recovery water injection development programs. This study includes tortuosity/ heterogeneity quantifications from imaging 2D technology which is valuable in understanding vertical/ horizontal fluid movements.

The authors feel that this study will narrow the gap in understanding contact angle wettability, heterogeneity characterizations from static conditions viewpoint and hence, the reservoir crude oil recovery vertical profile history from vertical rock samples.
Intelligent Course Recommender for Professional Development
Authors: Al Mudaifer Danah Adel , Al Qahtani Rahaf Salem , Veettil Tharayil Sarafudheen , Almass Abdulaziz , Dursun Serkan
Published: March 2023

One of the major challenges faced in oil and gas industry today is talent management of its workforce. Training the workforce and suggesting the right training courses to the individuals is important in talent management and career development. There are many training recommendation systems available using different machine learning approaches such as collaborative filtering, neural networks and hybrid models. In this paper, an intelligent recommendation system is proposed by blending machine learning algorithms, natural language processing (NLP) and text analytics combined with organizational preferences. This framework gives a recommender system considering the user profiles, training preferences for his or her organization where each set of organizational units will have unique training recommendation requirements considering organizational functional behavior. The proposed mechanism uses machine learning algorithms at different stages of its learning process and ensemble them in a unique fashion such that desirable results are achieved to the user satisfaction.
Factors Affecting CO2 Absorption in Water Using a Gas Absorption Packed Column
Authors: Al Hadhrami Maitha Zuhair , Alalaween Mohammad Abdel Fattah , Mateo Antonio Lugay , Al Blooshi Abdulmajeed Abdulla , Kahoor Khalid Yousuf , Al Yileili Saeed Ali , Al Suwaidi Rashid Salem
Published: March 2023

Population growth is directly associated with increase in energy demand. Amplification in industrial activity has led to a drastic escalation in greenhouse gas emissions causing global warming. The major gas involves carbon dioxide, accounting for 76% emitted from different industrial sectors. The oil and gas industry alone is responsible for 90% of these emissions. Removing CO2 is a vital process in the gas industry which must be undertaken. Carbon capture utilization and storage (CCUS) technologies have evolved through the years due to the necessity of the current world-wide shared goal, to attain net zero.

Several combustion methods have been developed to capture CO2 during actual operations at fossil fuel power plants, at natural gas processing plants and at coal gasification plants. However, methods that are based on chemical and physical absorptions have been most widely used. One example is the gas absorption-based method which requires low energy consumption and has been proven to be cost-effective. Using certain water types, mixed with minute concentration of chemical solvent, it can readily absorb CO2. This approach will be used in the following research study to investigate gas absorption rate using different water samples that pass through a packed column, thereby enhancing the mass transfer of gas component.

In this study, the gas absorption experiments were carried out using SOLTEQ gas absorption unit containing DN 80 packed column with glass Raschig rings and with an effective column height of 1000 mm (Figure 1). Under constant operating conditions, the temperature and pressure were set to 24°C and 2 bars, respectively, to investigate the impact of pH level and conductivity of various types of water on CO2 absorption at different gas flow rate.

The statistical analysis indicates that TDS and conductivity have a stronger correlation with gas absorption (P=0.99) than pH (P=0.76). The average CO2 absorption of the three samples at different flow rates (e.g., 0.8, 1.3, and 2.2 LPM) ranged from 36.40 in sample 1 to 69.50 in sample 2 at flow rate 2.2 LPM. Overall, samples 2 and 3, neutral to base with pH value of 7.25 and 8, respectively, have a statistically significant negative correlation with average CO2 absorption, whereas the acidic (pH = 5.42) sample 1 has significant positive correlation between the two variables (R2 = 0.99).

Overall, samples 2 and 3, which are neutral to base with pH values of 7.25 and 8, have a statistically significant negative correlation with average CO2 absorption. In contrast, the acidic (pH = 5.42) sample 1 has a significant positive correlation between the two variables (R2= 0.99). This study provides optimal operating conditions for the CO2 absorption process. However, additional research is required to investigate the effect of other physical and chemical properties of water on CO2 absorption.
Probabilistic Well Production Forecasting in Volve Field Using Temporal Fusion Transformer Deep Learning Models
Authors: Al-Ali Zainab Al-Ali Hussain , Horne Roland
Published: March 2023

Accurate well rate forecasting is critical for field development. In the oil industry, recurrent-based deep learning models have been used for production forecasting. Modern research is shifting towards using the novel transformer architecture in natural language and time series applications to better handle long-term temporal dependencies using attention layers. In this paper, we present a novel approach of applying a transformer-based deep learning model for probabilistic production forecasting.

The Temporal Fusion Transformer (TFT) model, a modern transformer-based model for time series forecasting, was used to provide a better oil rate prediction in the Norwegian Volve field. The historical bottomhole pressure, wellhead pressure, wellhead temperature and choke size opening real time series data were used as past input features in the TFT model to forecast ahead the oil rate of two wells. The model was trained with a quantile loss function to produce a probabilistic prediction with both upper and lower bounds of uncertainties. After optimization the TFT model was blindly tested on the last 20% of the data to evaluate its prediction performance compared Block Recurrent Neural Network architectures (BlockRNN).

The real-time production data used in this multivariate forecasting problem was found to be complex with no clear trend or seasonality. The BlockRNN model failed to produce a good prediction of oil rate compared to the TFT model. The TFT model was better at encoding the input features including, the choke size, wellhead pressure, and temperature, and understanding their long-range dependencies with the oil rate.The model was able to minimize the testing Mean Squared Error (MSE) for the two wells F-11H and F-12H reaching values of 0.08 and 0.03, respectively. In addition, the model was able to forecast a prediction bandwidth in between the 10th and 90th quantiles to account for uncertainty ranges which laid in-between the blind test intervals. Overall, the TFT model was proven successful in accurately forecasting complex trends of oil rates overcoming the limitations of conventional, BlockRNN uses a memory to understand and make predictions about new data models of information loss over long-term multivariate time series prediction.

Our work presents a novel approach of using the TFT probabilistic deep learning model for multivariate oil rate forecasting in the oil and gas industry. The model showed very promising results outperforming conventional BlockRNN-based models in addition to providing a range of the forecasting uncertainty using quantile regression. Knowing the uncertainty range helps in making critical decision particularly in the well intervention and field development.
Integrated Subtle Fault Prediction Technique Based on Seismic Conditioning and Deep Learning
Authors: Xin Chen , Jianlin Li , Min Zhao , Qunli Qi , Dengyi Xiao , Qiang Li , Li Wang , Fuli An , Weixiang Zhong , Bo Wang , Pengpeng Ye , Ziquan Su , Wenwen Yu
Published: March 2023

With the development of oilfield, the role of subtle faults becomes more and more important. Due to the limitation resolution of seismic data, it is hard for conventional methods to identify and predict subtle faults to meet the needs of reservoir development. In order to improve the accuracy of subtle fault prediction, a new fault prediction technique based on seismic conditioning and deep learning was proposed in this study.

The workflow mainly includes the following 6 steps: 1) Seismic conditioning based on regional stress and well data; 2) Forward modeling of fault models using different frequencies of wavelet, and get the seismic response sample for different throw fault; 3) Seismic attributes optimization based on the frequency and azimuth optimization for different throw of fault; 4) Fast fault identification and prediction for all different frequency and azimuth seismic data by using deep learning method; 5) Integrated the FMI and well data to optimize the different scales faults prediction results, and fusion of multi-scale faults. 6) Output subtle faults predict results after the subtle faults modeling and 3D QC.

The application of this new method in M oilfield in the Middle East shows that, the seismic data with higher frequency and NE-SW azimuth can better identify the NW-SE subtle faults. When the main frequency of seismic data is 30Hz, faults with a fault displacement >10m can be clearly identified, and when the main frequency of seismic data is 45Hz, faults with a fault displacement >5m can be clearly identified. Deep learning technology can quickly and effectively extract faults from seismic data. Fault optimization and fusion based on different frequency and azimuth seismic data can predict multi-scale fault system more reasonably. A series of small NW-SW faults are identified in the western part of the long axis anticline in the study area. These subtle faults cut the long axis anticline and formed a fault block traps with lower OWC in the southwest slope, which explains why the OWC and formation pressure in the west are different from east. 7 new wells drilled through the fault, also confirms the presence of NW-SE subtle fault.

The subtle fault prediction techniques based on deep learning and model forward modeling can better integrate the geological faults information into the deep learning model samples to improve the identification ability and prediction accuracy of multi-scale faults. The optimization of seismic frequency and azimuth can fundamentally improve the effect of deep learning and prediction of faults. High accuracy subtle fault prediction results can deepen reservoir understanding and improve for efficient oilfield development.
Carbonate Permeable Zone Cementing Practices and Challenges
Authors: Kareem Ali Ahmed , Ali Muhammad
Published: March 2023

Successful primary cementing operations are critical to long-term well integrity and well completion. The operator's Block-9 contract area is situated in the Southeast portion of Iraq. Wells drilled in Block-9 are primarily within the Yamama limestone reservoir. The Yamama formation is composed of four compartments (YA, YB, YC, and YD). The main production reservoir area is the YA; high-permeability characteristics and pressure depletion effects in certain layers are prominent in this compartment. In some wells, the cement quality across permeable and depleted layers of the YA presents challenges attributed to high pressure differential, early cement hydration, and microdebonding at the casing-cement interface. To achieve acceptable zonal isolation across these high-permeability and depleted layers, a thorough understanding of the issues is necessary. The operator's philosophy and procedures for cementing production casing to better understand the proposed solutions are discussed.

Cementing practices adopted in Block-9 in the past are discussed in addition to their impact on cement quality, current practices, and plans to address future challenges. To overcome this critical well integrity related challenge, a multifaceted approach was adopted. Offset well records, cement recipes, job execution, cement evaluation logs, and challenges faced during testing and production were reviewed in detail and are highlighted. Understanding these technical challenges and the formation response to cement slurry and hydration processes were key to designing cement slurries and job execution in such deep wells. Primarily, the operator focused on attempting to control/manage the cement hydration process and fluid-loss control across the permeable zones.

The proposed suggestions included understanding the permeable carbonate zones, high differential pressures, cement recipe design, cement additive impact, spacer and mud properties, pumping rates, casing centralization, casing rotation during cementing, the cement setting process, and cement evaluation log interpretation.

Lessons learned from this review can assist other operators globally with addressing similar issues with permeable depleted carbonate reservoirs and compromised cement bonding.