bluuebunny/crossref_metadata_2025 huggingface dataset:
Log Derived Novel Approach to Estimate Vertical Permeability in Multilayer Reservoirs Through Resistivity Anisotropy in the Natih Formation, Oman
Authors: Adetosoye A. A. , Moreno J. J. , Al Ghuzaily M. A. , Ulincy A. J. , Urazimanova A. M. , Samad A. , Barroeta R. G. , Portilla C. A.
Published: October 2023

For an oil reservoir subjected to waterflooding, the horizontal and the vertical permeabilities have a considerable influence on the areal and vertical sweep efficiencies. Particularly, in the case of the Natih formation – a multilayered and heterogeneous reservoir located in Oman – a new workflow is proposed to enhance vertical permeability estimation through resistivity anisotropy modeling, while also correcting Sw (water saturation) for resistivity anisotropy effects.

Permeability anisotropy (Kh / Kv) was measured in core samples taken from a vertical pilot hole and correlated with the resistivity anisotropy (Rv / Rh) inferred from inversions of LWD resistivity data in offset lateral wells. Also, by modeling phase-shift and attenuation resistivity measurements in the laterals, true horizontal resistivities are estimated and then used to obtain a more accurate Sw (water saturation). The Rv / Rh ratio of the laterals is used to infer Rv / Rh in the verticals and to generate the final Kh / Kv transform in the laterals. The corrected Sw as well as the estimated Kh / Kv ratio in the laterals are used as inputs to the field reservoir modeling.

Traditionally, when history matching waterflooded Natih reservoirs, the vertical permeability was assumed to be a fraction of the horizontal reservoir permeability. A Kv / Kh ratio, typically in the range of 0.1 to 0.3, was applied throughout the model. In the absence of core measurements, the Kv / Kh ratio was iteratively adjusted through trial and error, until a reasonable match of the historical production and injection data was achieved. The process was time-consuming, especially when history matching a large field. Through this new workflow, vertical permeability was estimated as an independent and variable reservoir property on a foot-by-foot basis along each lateral of the field. The new independent permeability was tested as an input in a dynamic model of a Natih reservoir in Oman, yielding results comparable to the traditional approach while significantly reducing the time to achieve history match.
Maximizing the Value of Transition Zone Reservoirs with Extra Deep Resistivity Measurements for Improved Field Development and Production Optimization–A Case History from a Marginal Field, Onshore Abu Dhabi
Authors: Ugonoh Mohammed , Makhiyanov Ruslan , Onyeije Raphael , Assreti Elamari , Suleiman Mais M. , Khader Ali A Sumayya , Aldhuhoori Hafsa Ahmed , AlSaadi Sami Abdalla , Potshangbam Sanathoi M
Published: October 2023

A rapid and a progressive high-water cut was observed in a newly drilled well within a transition zone reservoir. The horizontal section of the well was steered within the optimum zone based on porosity and water saturation cut offs in real time utilizing the standard logging and geosteering tools. Fluid distribution has always been an uncertainty in the model and mapping those boundaries is critical to future development strategy and production rates allocation.

A forward model was generated using the structural grids, well tops with definitive surveys of key nearby wells. In addition, extra deep azimuthal resistivity (EDAR) inversion feasibility evaluation was carried out to determine the depth of detection and distance to boundary to resolve multiple boundaries. In this challenging low resistivity environment, EDAR inversion would map an approaching conductive zone below the target and structural changes of the denser overlaying unit. A continuous thick oil column was mapped differentiating it from the conductive zone below in the entire horizontal section. Extra deep azimuthal resistivity technology was deployed as an additional requirement to mitigate the uncertainty due to fluid distribution and the thin net hydrocarbon thickness along the horizontal section. Based on evaluation results, the distance to the conductive zone below was mapped continuously in the entire horizontal section. The distance to the upper denser unit was also mapped and structural changes along the lateral section established. These inversion result facilitated optimum well placement within a 4 ft hydrocarbon column, increasing the production capacity of the well. The updated structure and the resistivity distribution along the wellbore were exported. This information would be integrated into the 3D model to further enhance the field development plan.

Typically, lower completion design is based on image logs, porosity and permeability plots for zonal isolation. However, in transition zone reservoirs, the proximity of water to the wellbore can have an adverse effect on well performance. When developing a field with uncertain fluid distribution, extra deep azimuthal resistivity can provide additional layer of protection by keeping the trajectory away from conductive zones in real time and assigning a realistic production rate based on mapped boundaries.
Workflow to Utilize Realtime Mechanical Specific Energy in Formation Tops Identification and Drilling Optimization in a Multilayer Heterogenous Mature Oilfield Offshore Abu Dhabi
Authors: Mendez Gutierrez F. A. , Ashraf M. , Perez D. R. Contreras , Al Dhafari B. , Landaeta Rivas F. , Krikor A. , Nakano S. , Andrews K. , Al Zaabi M. , Toki T. , Aragon J. C. Vega , Nishikori S. , Fukuda K.
Published: October 2023

Mechanical specific energy (MSE) curves are modelled from Real-Time (RT) data for daily follow up by Drilling engineers and Operation geologists to identify the efficiency of the drilling process and optimize the surface or downhole parameter to improve the rate of penetration (ROP) and accurately determine the formation tops interfaces. However, the manual process requires some time, resulting in a less efficient decision-making process, as well as drilling optimization and parameters standardization. Therefore, in order to increase the level of automation, monitoring efficiency and to simplify the overall process, a new methodology of selecting formation tops through MSE is proposed by a major offshore operator in UAE, using the benefits of RT data.

The applied methodology was to select a sample of 20 wells with 8 ½" mother hole section drilled across the different multi-layered heterogeneous reservoirs including both permeable and impermeable dense sublayers. For the selected wells, the RT recorded drilling parameters, LWD logs and survey stations were used in addition to the directional drilling BHA data such as sensor offset, GR correlation, as well as both expected and actual formation tops and basic mud rheology values. The behavior of MSE across each one of the drilled sublayers was manually compared and tabulated against the actual formation tops to establish comparison values. The model will be loaded and tested using the available Machine Learning Algorithms (MLA) to test the accuracy of the formation tops identified against the standard methodology applied by operation geologists for formation top selection and once the best fit model has been selected, the Operator will proceed to implement the same through RT operations.
First Multi-Zone Single Trip Cased Hole Gravel Pack Workover Enabling Production from Existing Reservoirs in Brunei Brownfield
Authors: Newn E. , Lim J. , Mogga E. , Lopez M. , Lim C. , Adeyeba A. , Kolakalapudi M. , Fah G. Goh Kim , Xiong M. Yun Wei , Zou C. , Razali R. , Barretto G. , Gil J. , Dada O.
Published: October 2023

The design for this Multi Zone Single Trip (MZST) Cased Hole Gravel Pack system proves the successful implementation of MZST gravel pack in workover wells for the first time in Brunei. The challenges and key operational requirements for this system were to achieve:

Active sand control via individual gravel pack treatment for each zone. Optimized operational efficiency by reducing the number of rig hours during well execution. Isolation of the existing reservoirs during gravel pack treatments with Maintain forward circulation capabilities during tripping in hole (for well control) Production access from existing reservoirs below the gravel pack Selectivity/mechanical isolation of production from each zone post-completions

The conventional method for multizonal gravel pack completions would be via a stack pack; multiple runs of perforation, wellbore clean up, and single zone gravel pack for each respective zone. With the deployment of this MZST system, a significant reduction (min. 40%) of trips can be achieved, thus increasing the value of the workovers. The other key aspect of the system is the use of specialized screens to reduce the number of components against a conventional gravel pack system, providing further operational efficiency.

The challenge of integrating the already established MZST system with workover wells is performing the gravel pack treatments without compromising/communicating with the existing reservoirs below. Novel modifications and procedural changes were made to the system to enable its compatibility with workover installations; temporarily isolating the existing reservoir during the gravel pack to later regain access during production, isolation strategies to minimize potential leak paths during execution as well as maintaining ability to circulate a potential influx from the reservoir, are among the implementations introduced by the team for this workover campaign.
Excellence Journey Towards Environmental Stewardship Through Circular and Sustainable Decarbonization, Ecosystem and Biodiversity Initiatives
Authors: Alhazzaa Mohammed S , Georgiou Ioannis , Ghanem Hashem H
Published: October 2023

This paper presents circular environmental initiatives at Abu Ali Island, Eastern Province, Saudi Arabia that led to sustainable and systematic decarbonization, ecosystem, and biodiversity programs. The prosperous ecological system in the Island makes it an excellent hub for wildlife, marine, and birds. The organization environmental initiative programs are: Contribute a net zero-carbon emission by reducing and offsetting greenhouse gas emissions.Support Saudi green initiative through mangrove plantation in the Island.Adapt carbon circular economy (CCE) approaches to turning wasted materials into valuable products.Enhance biodiversity in Abu Ali Island to create an integrated ecosystem.

Mangrove forests were a primary driving force behind the island's preservation efforts. The island is home to one of the biggest mangrove ecosystems in the region, with more than 5 million mangrove trees. In 2022, the island embraced the Kingdom's largest mangrove plantation program in a single phase, with a total of 3 million seedlings planted in the mangrove nursery at the island. This new record suppressed previous record held by the organization, which was to plant 2 million mangrove seedlings in 2020. The quantity of mangrove trees contributes to carbon dioxide sequestration as scientific studies have shown that "Mangroves are also able to sequester C at a rate two to four times greater than mature tropical forests and can store three to five times more C per equivalent area than upland tropical," according to (Donato et al., 2011; Alongi, 2014).

Moreover, as part of the offsetting efforts, a fish hatchery facility is under development in conjunction with mangrove forests. The fish hatchery can produce up to four distinct fish species at once, with a capacity of 10 million fingerlings per year. To boost local fish stocks, fish will be released into the Gulf. One of the circular economy's principles is to extend product lifetime. The team decided to utilize eleven decommissioned subsea pipelines — after decontamination and cleaning — as artificial coral reefs. Rather than removing these pipelines, which would result in high expense, they were cut into 10-meter sections and kept on seabed to be colonized and transformed into coral reefs. Some of the identified measures as CCE are the reuse of produced sanitary wastewater for irrigation and composted food waste as fertilizer to benefit the plants, and help reduce our environmental footprint.
Optimizing Industrial Risk Management Through AI and No-Code Platform: A Global Solution for the Oil and Gas Industry
Authors: Fortunato H. E. , Marcomini K. , Soares G. J. , Gremes M. F. , Alberto P. F. , Reis F. J. , Abbas C.
Published: October 2023

Effective risk management is critical in the gas and petroleum industry, ensuring worker safety, environmental protection, and business continuity. To improve risk management, an artificial intelligence-based system has been proposed that can identify objects and situations of risk from camera images. The system includes an alert algorithm and report generation for auditing, increasing accuracy and efficiency in oil industry operations. In addition, a no-code system has been developed, which can be customized by inserting new risk events using tools such as creating polygons and allowed and prohibited logic, and text searches to find new items in captured scenes. The system was trained by defining the objects and events to be identified, including the use of personal protective equipment, eyewash stations, handrails, fire extinguishers, prohibited areas, and vehicles traveling above the permitted speed limit. A database was created, supplemented by images from the YOLO convolutional neural network architecture, version 7, for the development of machine learning. The model was then trained, tested, and validated. The software and no-code platform were subsequently developed for the study scenario. The proposed system is scalable, versatile, and has a global territorial scope, making it suitable for various industrial monitoring situations. It can be replicated for multiple plants and customized by adding new events as required. The platform can work remotely without local servers and offers access management by registered users. The proposed system is unique, with integrated functionalities, such as vehicle speed detection, action, object, and equipment identification, and report and alert generation. The system reduces monitoring costs, is not dependent on human supervision, and can detect deviations made by employees, thus enhancing problem resolution and prevention. Finally, pre-installed cameras can be used, and the system offers customization possibilities for various industrial areas.
Characterization of Pore Structure and Fluid Saturation of Organic-Rich Rocks Using the Set of Advanced Laboratory Methods
Authors: Mukhametdinova A. , Andreyev B. , Latypova M. , Kalmykov G. , Kalmykov A. , Bogdanovich N. , Spasennykh M. , Cheremisin A.
Published: October 2023

The global shift in energy reserves structure, including Russia, is moving towards the effective development of unconventional oil and gas reservoirs (EIA 2013). However, the problem of assessing hard-to-recover reserves in low-permeability, organic-rich reservoirs still lacks a comprehensive solution. This is primarily due to the lithological, physicochemical, and reservoir properties of the rocks, and often results from the utilization of a limited set of laboratory techniques that yield different values for the same measured property. Several studies on various aspects of unconventional reservoirs also emphasize the necessity of employing alternative techniques for laboratory analysis of core samples (Handwerger et al. 2012; Yuan et al. 2019; Curtis et al. 2012).

Currently, the depletion of oil and gas reserves in traditional sandy reservoirs has made the search for new hydrocarbon deposits increasingly important. A significant area of focus in this regard is the study of potentially productive intervals within unpromising kerogen-clay-siliceous strata that are rich in organic content. One notable example of such intervals is the high-carbon Bazhenov formation in West Siberia (Ulmishek et al. 2003; Kontorovich et al. 1997). Modern field development methods, such as hydraulic fracturing (HF), the use of organic solvents, and thermal recovery, have enabled increased production from high-carbon formations with low reservoir properties. However, in order to make accurate predictions for the development of high-carbon formations using modern methods, it is crucial to accurately describe the complex void space system and understand the relationship between hydrocarbon compounds, water, and the solid rock matrix. Otherwise, it is impossible to predict the behavior of the void space following anthropogenic interventions using modern field development techniques.

To date, several methodological recommendations and approaches have been developed for assessing oil resources and calculating reserves in Bazhenov formation deposits (Bilibin et al. 2015; Petersilye, Komar, et al. 2016; Prishchepa et al. 2015). However, these methodological recommendations should be carefully adjusted depending on the type of formation, the degree of organic matter (OM) transformation in high-carbon formations, and other factors. Factors such as macro- and microlithological characteristics of the section, mineral composition, reservoir properties, type, maturity, and amount of OM in the rock, morphology of the pore space and its hydrocarbon (HC) filling, the presence of free and bound water, and wettability, among others, should be initially included in the fluid dynamic model. These factors form the basis for refining existing methodological recommendations.
The Wiggle that Makes a Difference: Using AI to get the Right Wavelet with Multi Well Input
Authors: Alkhanjari H. S. N. , Glukstad M. M. , Alqassabi S. H. , Alrubaiey A. , Ali N. , Albadi O. A.
Published: October 2023

A common problem when carrying out seismic interpretation in the Two-Way travel Time (TWT) domain is to choose the adequate wavelet when performing well to seismic tie. This step is also crucial in any Quantitative Seismic Interpretation (QI) project where the use of the right wavelet makes a big difference. Many of the fields in Oman have several wells with the appropriate data, i.e., Time-Depth (T-Z) pairs or Check shot data (VSP) and Sonic, but the quality of the log data and the short extend of the Sonic log requires calibration, making it very challenging to select the right well for the analysis. The interpreter often looks at several wells, in the same field, but with different data and quality. Although multi-well to seismic tie is available in most commercial software, the problem of dealing with variable data quality, having to select the right wavelet, that will make sense for all the wells, is still a problem that is very time consuming and often difficult to resolve. The interpreter has to make a decision but lacks any proper quantitative or qualitative approach on which to base the choice of wavelet. Recently an Artificial Intelligence (AI) tool was released, Automated Seismic to Well Tie (AWT) in Petrel version 2021, which uses the seismic volume and well data to obtain the best wavelet which provides the best tie when generating the synthetic seismogram, with minimum effort, in matters of few hours. The tool looks at all the possible wavelets and defines the best match and ranks the outcome for the different wells. Crucial part of this methodology is to provide the computer with as clean as possible data set. The team tested this tool in field XX and with technical support from the software owners, obtained spectacular results in a very short time saving weeks of work.
Keep Your BHA Cooler While Drilling Through High-Temperature Formations
Authors: Alabdulmohsen Zainab , Al-Shubaith Abdullah , Anioke Chidiebere , Al-Saqer Qassem
Published: October 2023

Typically, drilling fluids exhibit lower rheological properties at elevated wellbore temperatures, which affect wellbore cleaning capabilities, filter cake stability, down-hole tools lifetime, and increase the possibility of stuck pipe events. Drilling through high temperature formations >300°F using oil-based drilling fluids often requires the use of mud coolers to help maintaining BHA tools and to reduce any risk of failures that can lead to high associated costs of non-productive time (NPT).

To overcome the above associated challenges, field experience introduces a flexible engineered approach. This approach is based on a lubricant that is an environmentally acceptable and as polymeric fatty acid solution for oil-based muds (OBM). From an operational standpoint, this solution induces a cooling effect of the mud hundreds of feet ahead without the need of circulating it or using a mud cooler. This lubricant worked to reduce the frictional effect resulting in temperature reduction while drilling and maintaining uniform rheological property of the drilling fluids. Also, a laboratory work was conducted using a metal-to-metal approach to approve the lubricity effectiveness of this solution in friction reduction.

An addition of 1-2% of the proposed lubricant to OBM system resulted in a drop in temperature by ~10°F. This paper aims to present the effect of drilling high-temperature wells >300°F which can lead to high potential of having failure in the measuring-while-drilling (MWD) system due to the equipment limitations. Furthermore, it shows how this lubricant solution could reduce circulation time to 50% per 1,000 feet and cool down MWD temperatures with torque reduction up to 6% compared to previous operations. Laboratory work also proved that this solution could provide friction reduction up to 23%.

This friction reduction provides lower downhole temperature profiles by adding OBM lubricant while drilling and has significantly assist in minimizing NPT, the probability of MWD failures, and insure a smooth operation.
Predicting Porosity from Drilling Data Using Machine Learning – Challenges and Solutions
Authors: Alhowaish H. A. , Mezghani M. M. , Shakriov A.
Published: October 2023

Porosity is key to understanding reservoir potential for hydrocarbons. The main methods of acquiring porosity data are through wireline logging or detailed laboratory measurements. Although informative, these operations are restricted by their economic and operational costs. Machine learning (ML) is a branch of artificial intelligence that uses input data to train a model and generate a prediction, saving cost and time. The objective of this paper is to predict well porosity with high accuracy and reliability with machine learning, using only drilling data.

This study utilizes a supervised ML method with a gradient boosting algorithm. Out of 10 wells, 9 are used for training which is split into a 9 to 1 ratio of training to testing, and another well for validation. The input parameters shown at each depth are conventional drilling parameters, such as weight on bit, revolutions per minute (RPM), torque, etc. Input parameters are preprocessed prior to filtering and clustering to enhance the model quality. The model performance is measured using root mean square error (RMSE) and mean average error (MAE). The model is then assessed using the validation well with the same metrics as the model performance.

The model training showed promising results in predicting porosity with the ML methodology. After preprocessing and parsing the data, clustering analysis is done to group data points based on their similarity. A permutation feature importance analysis revealed the input variables that contributed most to the outputs, mainly RPM and torque. The model's performance was also enhanced by modifying uncertain intervals in the input parameters to remove outliers and give a lower RMSE and MAE. We then investigated the difference between a model predicting porosity for a specific geological formation against a global ML model. A formation-based model takes input data from a single formation to predict porosity, while a global model takes input data from all formations to make a prediction at any point. Results show that a formation-based model is highly sensitive to the input data and number of wells compared to a global model. Next, we plan to improve the preprocessing techniques, include a sensitivity analysis, and evaluate the two models further.

Previous studies have highlighted the need to predict porosity at a more economically viable approach. But few have solely used surface drilling parameters in machine learning, which is extensively monitored at every borehole and can simplify ML models without reducing performance. This study demonstrates the effectiveness of using only drilling data in predicting porosity, proving beneficial to reservoir characterization and hydrocarbon exploration.
Gas Compositional Effect on Fit-For-Purpose CO2 Storage Capacity Estimation: A Case Study in Malaysian Depleted Clastic Gas Reservoir
Authors: Affandi R. A. , Yakup H. , Hendraningat L. , Jalil M. A. , Tewari R. D.
Published: October 2023

Amidst growing concerns about global warming and climate change, there has been increasing attention given to the storage of CO2 using underground geological structures. Depleted gas reservoirs have been identified as one of the most promising geological solutions for CO2 storage, owing to their data accessibility, economic feasibility, and safety. Currently, extensive studies are being conducted to appraise the CO2 storage potential of offshore Malaysian Depleted Clastic Gas Reservoir. The aim of this paper is to examine the impact of gas properties on CO2 storage capacity estimation in depleted gas reservoirs. The scope of the study includes a numerical simulation (Dynamic CO2 storage capacity) approach to model the behaviour of CO2 in the subsurface and to assess the significance of gas properties on the storage capacity of the reservoir. The Material Balance analysis (MBAL) method is employed in this study to model the potential CO2 storage capacity in the subsurface, taking into account the impact of gas properties such as z-factor and Gas Formation Volume Factor (Bg). The simulation process starts with history matching the historical data by using improved workflow. It eventually continued to forecast the production and CO2 storage capacity.

Gas properties, in particular z-factor and Bg, significantly impact CO2 storage capacity estimation in depleted gas reservoirs, mainly due to the dynamic of injected CO2 composition which is mixed with residual gas. The study observed that a gas properties difference (Bg at Pinit is from 0.0109 to 0.0122 ft3/scf) in the reservoir D resulted in a 15% difference in CO2 storage capacity, while for the reservoir I case, a difference in gas properties (Bg at Pinit of 0.00840 to 0.00894 ft3/scf) resulted in a 3% difference. Besides that, an improved technique for estimating fit-for-purpose CO2 storage capacity was established in this study by generating and assigning individual PVT models through flash and recombination processes for reservoir without sufficient PVT information. The models are matched to the initial saturation pressure using characterized fluid properties available in major reservoirs, resulting in a more accurate and effective estimation of CO2 storage capacity. The study concludes that, when using the Material Balance analysis method, gas properties must be considered and properly characterized for better understanding and accuracy of CO2 storage capacity estimation. This paper provides new insights into the role of gas properties (z-factor and Bg) in CO2 storage capacity estimation. In addition, this work has improved the workflow for fit-for-purpose CO2 storage capacity estimation using Material Balance analysis. The results of this study provide a fresh perspective on the optimization of fit-for-purpose CO2 storage capacity estimation.
New Form of Skin Due to Flow Convergence Towards Perforation Intervals in Hydraulically Fractured Wells. Is Perforation a Concern Post Fracturing?
Authors: Samy A.
Published: October 2023

Total skin includes different components which may contribute to the additional pressure drop around wellbore due to formation damage, perforation, partial penetration, well deviation, two phase flow, stimulation (or fracturing) and non-Darcy flow. Even though successful frac jobs usually yield incremental production gains, there are other skin components which can cause positive skin and reduce the potential (ideal) incremental gain post-fracturing such as fracture face skin and choke skin in horizontal wells with transverse fractures. There is a common understanding that perforation is important for frac execution only but not a concern during production post-fracturing because well productivity will be dominated by fracture conductivity. However, this paper shows other form of skin which can impact well productivity post-fracturing due to flow convergence inside fracture towards perforation intervals.

The method is to calculate the additional pressure drop and the associated skin due to radial flow convergence inside fracture towards the perforation holes. The method considered the effective flow area which is in communication with fracture wings, and it depends on perforation density, effective entrance hole and gun phasing. The procedures include modification to the flow equation which describes choke skin due to well orientation in transverse fractured wells.

This paper shows that perforation is a concern and can impact well productivity post-fracturing especially in moderate to high permeability formations. This skin component should be considered in estimating flow rate post fracturing in order to avoid over-estimation of well productivity. Also, it discusses the importance of adding perforation intervals post-fracturing to enhance well productivity and the optimum conditions / circumstances that requires adding perforation post-fracturing.

This paper presents a new form of skin which should be considered during well design and frac design. By avoiding this skin, well productivity post fracturing can be significantly increased.
Numerical Simulation of Proppant Heterogeneous Distribution in Shale Gas Reservoirs
Authors: Hou Tengfei , Zhang Yang , Shang Litao , Zhang Shiling , Xiao Fengchao , Bai Haoli , Sun Xun , Qiao Yan , Xu Gang , Zhang Qingyao
Published: October 2023

Slickwater fracturing with high injection rate and large volume has been widely used in the development of shale reservoirs, while the proppants cannot distribute uniformly in fracture networks, usually in the forms of sand-bed, separated pillars and local displacement. Thus, there are still some key issues need to be figured out for better fracturing design, such as the proppant placement status in complex fractures, and how to achieve effectively propped fractures, etc.

In this paper, a three-dimensional proppant transport model is established by Dense Discrete Phase Model (DDPM). The flow field and concentration distribution of the proppants were analyzed, by tracking the trajectory of proppants in different types of complex fractures. Besides, the placement status of particles in the primary and secondary fractures was analyzed. In addition, we also conducted the research on proppant transportations in perf clusters. Finally, according to actual fracturing treatment schedule, three different sizes of proppants were gradually injected and the distribution law of the proppants was studied.

Based on the concentration distribution of proppants in the complex fractures, fractures can be divided into four zones: pure fluid zone, critical suspension zone, flowing slurry zone and settling bed zone, while the critical suspension zone and flowing slurry zone of secondary fracture are smaller than primary fracture. Besides, the proppants concentration entering into the fractures far from the entrance is more than that entering the fractures near the entrance. The ratio of proppant concentration into each perf cluster (3 clusters per stage) is about 1:1.5:2, while that concentration ratio is 1:1.25:1.6:2 in four clusters per stage scenario, while the proppant concentration is inversely proportional to the amount of proppant and liquid injected. The proppants of 100 mesh injected in the early stage migrates to the far end of the fracture, and some enters into the branch fractures, while most of them settled in the sand bed of the main fracture. Meanwhile, the following 40/70 mesh proppant injected is mainly distributed in the main fracture at flowing slurry zone. The 30/50 mesh proppant injected in the later stage is mostly located at the fracture entrance and at the top of the sand bed. Finally, it was found that high injection rate, small particle size, and low-density proppant could improve proppants preferentially entering branch fractures.

This paper provides a clear insight of proppant distribution law in complex fractures under field fracturing treatment schedule. And our model can be used to optimize the fracturing treatment design.
Valve Leakage - How Acoustic Emission and Artificial Intelligence Can Reduce Losses and Increase Safety and Efficiency in Oil and Gas Plants
Authors: Hettegger Michael , Berezovsky David
Published: October 2023

The paper provides an overview of the current challenges of valve inspection in the industry and how they can be overcome with the help of software and artificial intelligence. Studies show that 5-10% of valves in oil and gas plants are suffering from internal leakage which can lead to economic losses, health and safety issues or potentially to environmental pollution. Acoustic emission testing is a relatively modern but already well-established technology for leak detection in valves, however existing solutions show some limitations. These are among others e.g., their complexity of use, they need trained and experienced personnel, the time required to perform analyses and the use of solely proprietary and closed devices. Interviews with experts performing inspections in the field have shown that they are facing challenges such as using the right measuring points, finding the right duration of measurement, applying the right pressure when placing the sensor and finally transferring data and interpreting the results. Research has shown that interpretation of results depends very much on experts' know-how (Singh, Saleh Al Kazzaz, 2003) and reproducible results have thus been difficult to achieve. This causes the difficulty for companies to use the data for further purposes, such as predictive maintenance.

To address this problem, over 2000 measurements in laboratories and simulated leakages in the field have been collected, taking into account different media/pressures/different valve sizes/nominal diameters and valve types. The experience gained and the data collected were used to build a smart and mobile inspection system which is able to standardize inspection processes for leak detection in valves. It was built on the well-established acoustic emission technology, extended with digital features.

Our digital approach has proven that a standardized process is able to significantly reduce the dependence on expert knowhow. By combining AE signals with state-of-the-art signal processing, algorithms and machine learning models, the vast amount of AE signals can be processed within seconds, providing reliable results even in noisy environments. These developments provide companies a new opportunity for in-house valve inspection, a possibility to fight against shortage of skilled labour and increase the reliability of their assets.
Remedial Alcoholic Condensate Banking Treatment in Deep Gas Wells in the Sultanate of Oman
Authors: Al Aamri Ghusun , Al Yaaribi Ahmed , Al Hinai Adnan
Published: October 2023

One of the most gas production challenges from tight gas reservoirs in the sultanate of Oman is condensate banking. Such a phenomenon usually results in sharp declines in gas and condensate production after reaching the dew point, and becomes more influential in the unconventional and depleted condensate-gas fields. Another challenging aspect is the complex and expensive post-drilling and post-fracturing cleanout due to the high capillary pressures slowing the completion brine flowback. Successful field applications developed with alcohol treatments in deep tight sandstone gas wells have minimized the impact of condensate banking on production in the Sultanate of Oman.

Thorough lab testing and screening processes to optimize the formulation of the treatment and maximize the chances of success were conducted prior to taking the application to field implementation. In particular, the solvent type and concentration were selected carefully to avoid any precipitation issues that might arise from incompatibility between the alcohol treatments and the highly saline formation water. In addition, careful HSE planning was required before the field deployment due to the low flash point associated with such treatments.

A campaign of 4 field trials was conducted on several gas wells that are impacted by condensate banking. For the condensate banking, the treatments managed to restore the gas production from closed-in wells while increasing the condensate rate by more than 170% and gas rate by more than 220%. These promising results have resulted in planning a wider deployment scope to further test the operational limits of the alcohol treatments and optimize the production from several fields that are impacted by condensate-blockage impairment.

Using this alcohol treatment as an alternate to traditional water and condensate blockage remediation has improved efficiencies in time, production and materials. The application provides a more economical means to enhance production in tight gas fields of the Sultanate of Oman.
Sustainable Aviation Fuel Investment and Feedstock Calculations by Microalgae Applications with Biorefinery Approach
Authors: Özdemir Irmak
Published: October 2023

Numerous studies have been created in recent years to establish a sustainable biofuel production industry to address the depletion of fossil fuels. This new industry must be effective (high productivity), financially successful (low production costs, which leads to reasonable fuel rates), and moral (low carbon balance).

Algae, one of the most significant sources of biofuel, can survive in a variety of ecosystems, including those found in freshwater and marine environments, desert environments, hot springs, and glacial environments. The kinds and combinations of photosynthetic pigments present in various algal species decide the systematics of algae. Microalgae have enormous potential for the creation of sustainable biofuels.

The expense of aviation fuel would approach economic viability if algae production could be scaled up to commercial levels, which would also result in a reduction in carbon emissions. That is more than enough motivation to compete with petroleum fuels, particularly when paired with existing policy support or consideration of coproduct opportunities, as well as promises from the international community to decarbonize aviation.

The study's objective is to use wastewater effluent to harvest biofuel from algae specie. Studies will be done in this context on the physiological and chemical characteristics of Arthrospira Platensis. Also, it will research and interpreted how much investment and feedstock is required if the airlines use sustainable aviation fuels.
Emphasis of High Order Stratigraphic Sequences Enabled by the Relative Geological Time Modelling Method: Application to Fractured Thin Reservoirs in a Pre-Salt Gas Field, Offshore Netherlands
Authors: Daynac N.
Published: October 2023

The author describes the method and results of a global and automated approach for seismic interpretation (Pauget et al, 2009), applied to a pre-salt gas field of the Dutch Cleaver Bank High platform, offshore Netherlands. A sequence stratigraphic framework called ‘Relative Geological Time (RGT) model’ is built from the seismic data to emphasize structural and stratigraphic features. Basin and reservoir characterizations are thus enabled by RGT-derived advanced attributes, rock physics modelling, Wheeler diagrams and sub-sample stratal slicing. Several fault networks related to different tectonic phases are emphasized, key stratigraphic surfaces are delineated, and major facies trends of the pre-salt reservoir level are discriminated. Those outputs are finally used to assess the impact of fault networks and subsequent subsidence on the eustasy-controlled thin beds succession. The author ultimately demonstrates the potential of the global RGT modelling method to revise hydrocarbon fields and identify pre-salt siliciclastic carbon storage sites.
The Use of Artificial Intelligence (AI) to Give Insight to a Complex Well Tubing Issue to Ensure Suitable Corrosion Mitigation Approaches
Authors: Mohamed-Said M. , Cowe B. , Bertoncello A. , Oliveira-Martinez F. , Galliot L.
Published: October 2023

In one of TotalEnergies North Sea fields, nitrate is continuously injected as the main mitigation of reservoir souring. The nitrate treatment is employed to limit the biogenic generation of H2S, due to reservoir souring. Reservoir souring is caused by the proliferation of SulfateReducing microbes (bacteria and/or archaea).

In parallel, severe corrosion was observed in oil producing well tubing conveying fluids from a reservoir subjected to nitrate treatment. It is known that nitrates can catalyze the corrosion of carbon steels through different mechanisms, in particular electrochemical or microbiological. The challenge was therefore to accurately evaluate the impact of nitrate injection, and its presence in the produced fluids, on the corrosion of the producing well tubing.

The influence of nitrate treatment towards corrosion of carbon steel well tubing has been singled out using an artificial intelligence algorithm. The algorithm employs a method called "Propensity Score Matching" (PSM). PSM is a statistical method commonly used in the medicine field to assess the efficiency of treatment in biased data. This method has been used to compare two reservoirs, one being subjected to nitrate treatment and another that has never been subjected to nitrate treatment.

In this paper a first known use of causal inference in industrial settings is presented. It helped removing biases by comparing only comparable data and to find causal relationship in the data. Outcomes of the multi-faceted study have led to optimized corrosion mitigation approaches and increased well tubing service life.
Learnings from 150+ Autonomous Inflow Control Completions in 7 Unique Reservoirs in Sultanate of Oman
Authors: Ali Al-Jumah , Mahmood Harthi , Said Kindi , Yousuf Sinani , Nasser Azri , Ahmed Al Lawati
Published: October 2023

This paper summarizes the integrated subsurface technical learnings from the successful application of Autonomous inflow control Completions in long horizontal wells producing heavy oil in multiple fields in the south of Sultanate of Oman, it details the facts, observations, and insights the multidisciplinary authors have captured through initially piloting 4 trials to executing over 150 jobs in 7 unique reservoirs in the last few years utilizing multi-vendor equipment.

The technology in principle can precisely identify the fluid flowing through it and shutting-off the high water or gas saturated zones autonomously while stimulating oil production from healthy oil-saturated zones. The Autonomous Control valves can differentiate the fluid flowing through it via fluid properties such as viscosity and density at reservoir conditions, with a design based on Hagen-Poiseuille and Bernoulli's principles.

Based on the Integrated performance reviews, the technology has shown the benefit of accelerating oil production as well as reduction of unwanted water which not only reduces the OPEX of these wells but at the same time has an enormous positive impact on the environment and Green House Gases (GHG) emissions. Majority of the wells completed with this technology started with a relatively lower water cut and are still producing with low water cut and higher oil production as compared to other direct analogs neighboring wells. Also, from initial field-wide assessment, it is envisaged that this technology will assist in producing more oil sooner i.e. acceleration, improving overall recovery v time. Also, the technology helped in mitigating the facility constraints of handling produced water which allows the continued drilling of field development activities to drill in-fill wells. Only installations in New wells will be discussed here.

The multidisciplinary authors have summarized the results from this technology deployment in multiple oil fields and presented it in this article as a practice worth replicating in a similar heavy oil environment, due its many benefits in optimizing field development and performance. This article will not focus on the theory and design of the technology, but rather the practical aspects of implementation and the impact on wells performance. Please refer to "further reading" for details on theory as well as more info on installations in existing wells.
Qualification of an Emerging Class of AICDs with Artificial Gravity: The Density-AICD Technology
Authors: El Mallawany Ibrahim , McChesney Ryan , Greci Stephen , Novelen Ryan , Corona Georgina , Warren Caleb , Asthana Pranay , Bukhamseen Ahmed
Published: October 2023

Conventional Autonomous Inflow Control Devices (AICDs) use the downhole viscosity contrast between wanted and unwanted fluids to preferentially produce one while restricting the other. Effectivity of these conventional AICDs is limited in light oil reservoirs where the difference in viscosity between oil and water is small or nonexistent. This paper describes an autonomous device that allows or impedes flow based on fluid density. It also presents the qualification testing program completed to advance the Density-AICD from a development concept to a commercially available product.

The Density-AICD distinguishes between produced fluids at downhole conditions using an innovative buoyant float design with an effective density between oil and water. Production flow through the device generates an artificial gravity, amplifying the buoyant force used to control the Production Valve altering the tool's inflow rate. The fluid selector feature operates independent of Earth's gravity eliminating the need for downhole orientation in the completion.

The performance of this novel tool has been demonstrated through computational numerical simulations, small scale sub-component testing, and a full-scale qualification test program. Sub-component and system level tests performed to evaluate fit for purpose and reliability included: Production Valve cycle and erosion testing, bearing erosion testing, National Association of Corrosion Engineers (NACE) component testing, pressure testing of a wash-pipe-free feature, system erosion testing, and flow performance for single and multi-phase flow.

Density-AICD flow loop testing demonstrated substantial restriction to unwanted fluids based exclusively on density contrast. Test data showed a higher ratio of oil to water production than the initial design requirement and confirmed the ability of the device to toggle between open and closed positions depending on the surrounding fluid. A subsequent flow and function test was conducted after subjecting the tool to erosion testing with a negligible effect on performance and functionality.

This paper will present the activities completed to qualify the Density-AICD technology and the benefit of the technology in very-light oil reservoir applications.