bluuebunny/crossref_metadata_2025 huggingface dataset:
Deployment and Performance Analysis of Gas Handling ESP Systems in a High GOR Environment
Authors: Alsinan Y. M. , Alali M. H. , Fardan A. A.
Published: February 2024

The rise of gas handling devices for ESPs has been crucial for high GOR environments. These devices aim to efficiently manage high gas volume fractions (GVF) to mitigate gas locking, which can cause frequent ESP trips, by homogenizing the fluid before entering the pump. This paper aims to provide a performance analysis on the effectiveness and capabilities of gas handling ESP systems, elaborating on the technology, mechanisms and the various deployed designs, including their success in enhancing wells’ performances and production rates.

To achieve optimum production conditions and well deliverability, ESPs with gas handling devices have been installed in numerous high GOR wells. All the ESP designs have been meticulously analyzed through multiple simulation models to optimize the design parameters, in addition to evaluating the performance of the well before and after the ESP installation. The study incorporates analysis of various ESP designs in terms of rate, GVF, and pump setting depth. The gas handling systems were tested across different conditions for thorough performance analysis and technology evaluation.

The performance analysis shows that the productivity of some wells has had a fivefold increase, while the maximum GVF the deployed gas handling systems can withstand is close to 55%. It's important to note that the ESP system functions better with higher intake pressure due to a more controlled GVF, meaning that a deeper pump setting depth is preferred when possible. Overall, the gas handling ESP installations have exhibited remarkable and promising results by substantially boosting the well deliverability and rate potential of their respective producers. Since conventional ESPs cannot withstand high GVF and tend to gas lock, eventually leading to pre-mature failure, this technology mitigates such failures and presents a reliable artificial lift method for high GOR reservoirs.

The deployment of ESPs with gas handling systems is proving to be a great success for significantly enhancing the production of high GOR oil producers requiring artificial lift. Hence, this study presents a reliable method to increase well deliverability, and confirms the advancement of the emerging technology as opposed to the conventional ESPs that cannot withstand high gas fractions.
Research on the Construction of Petroleum Software Cloud Platform Based on Distributed Architecture
Authors: Song Mengxin , Feng Mei , Wang Chengci , Miao Hongping , Feng Defu
Published: February 2024

Researchers in exploration and development (E&D) field need several professional software resources for data processing and analysis. Enterprises can achieve cloud-based usage and shared management of petroleum exploration and development software through the deployment of cloud platforms. With the increasing demand for remote and overseas collaborative research, the single-node cloud platform deployment mode no longer meets the needs of collaborative research. This paper proposes a construction scheme of cloud platform for petroleum software based on distributed architecture, which realizes the unified management of software research environment, software licenses, and data. The proposed architecture has been implemented in a division of CNPC, realizing the cloudification of more than 20 mainstream professional E&D software applications such as Petrel and LandMark. By establishing central sites in Beijing and branch sites in Dubai and Hangzhou, the researchers are provided with a cross-regional collaborative research environment on the cloud, thereby enhancing the research efficiency, improving the efficiency of cross-regional collaborative research, and facilitating the unified data management and the digital transformation of petroleum enterprises in the cloud environment.
The Nature of the Interaction Between Bit-Whirl and High-Frequency Torsional Oscillations
Authors: Hohl A. , Kueck A. , Kulke V. , Glowatzki K.
Published: February 2024

High-Frequency Torsional Oscillations (HFTO) are bit induced self-excited vibrations which can cause downhole tool failures and reduce the reliability of downhole tools. It is essential to understand the interaction of HFTO with other vibrational phenomena to develop effective HFTO mitigation strategies. While coupling with axial vibrations and stick-slip have already been studied extensively, the interaction of HFTO with lateral vibrations has received less attention. This paper analyzes this interaction based on a bit rock interaction model that accounts for the superimposed movement of whirl and HFTO at the bit.

The excitation of HFTO can be attributed to a velocity-dependent characteristic of the cutting torque. A model that incorporates the superposition of lateral and torsional movement at the bit is used to calculate the velocity-dependent bit torque based on three components: the cutting velocity at each cutter, the normal force distribution along bit blades, and velocity-dependent forces between the bit and the rock. The velocity distribution is based on a kinematic model that superimposes the lateral motion of whirling and the rotational motion of HFTO. The normal force distribution is derived from the bit blade and cutter configuration, and the velocity-dependent force characteristics at each bit element is based on findings of laboratory tests with single cutting elements. A continuous multivariable function determines the nonlinear drilling torque characteristic depending on the amplitudes of HFTO and backward whirl.

Evaluation of the simulated drilling torque shows that HFTO cannot be excited in presence of bit backward whirl. Specifically, it was found that an increasing rate of bit backward whirl leads to a bit torque characteristic generating less energy input or even energy output to HFTO. This is caused by backwards cutters with negative cutting torques corresponding to high energy dissipation. Forward whirl, on the other hand, cannot suppress HFTO. Comparison with laboratory data confirms these results. Cutter geometry and normal force distribution do not appear to have a significant effect on the results in either case.

The new bit model provides a physics-based explanation of why bit backward whirl and torsional vibrations cannot be observed simultaneously. The influence of parameters, like the cutting-edge geometry, can be evaluated much faster than, for example, with particle or finite element models.
Optimize Computational Throughput of Reservoir Simulation Workflows in a GPU Based High Performance Computing Environment
Authors: Soffientini S. , Panfili P. , Ferrari A. , Dovera L. , Rossa E. Della , Fragola D. , Abbate E. , Ortega A. , Rosa A. , Khait Mark , Zhang Yongpeng , Cominelli A.
Published: February 2024

Decision making workflows in the energy industry require the capability to simulate hundreds if not thousands of models in a practical timeframe. In this paper we show how these capabilities can be achieved by exploiting top-class high performance computing resources available on premise.

A GPU reservoir simulator can maximize the efficiency and effectiveness of computational kernels for solving partial differential equations and phase equilibria on modern devices, hosting thousands of floating-point units with an unprecedented memory bandwidth. It incorporates functionalities to model recovery processes, and includes capabilities for coupled reservoirs and network simulation. Recently, we added the possibility to exploit GPU Multi Process Service and run field scale, multiple-reservoir simulations on a single device.

The Simulator enables the possibility to simulate multi-million cell models on a single GPU, and then execute reservoir workflows where ensembles of many hundreds of models may run altogether, maximizing the overall throughput. In this work we present the most relevant applications of a specific GPU reservoir simulator, highlighting its efficiency and effectiveness in tackling everyday business requests and the benefits it provides with respect to traditional CPU-based software. In more detail we will show the application of the tool for the simulation of: 1) an uncertainty quantification of a compositional dual porosity-dual permeability super-giant carbonate reservoir; 2) the history matching of a black-oil reservoir through ensemble multiple data assimilation followed by screening and optimization of injectors location; 3) revisiting an integrated asset model uncertainty quantification including five black-oil reservoirs. This work demonstrates how the availability of a GPU centric reservoir simulator combined with high performance computing resources was instrumental to the deployment of the most complex and computationally intensive workflows processes inside our Company. The process combines focus on the leading-edge company hardware and care on current company needs.
Underground Hydrogen Storage in Saudi Arabia: Opportunities and Challenges
Authors: Alanazi Amer , Ye Jing , Afifi Abdulkader , Hoteit Hussein
Published: February 2024

Hydrogen (H2) is anticipated to play a crucial role in Saudi Arabia's transition to a low-carbon economy as an alternative clean fuel. The conversion of fossil fuels through steam methane reformation produces blue H2, with captured carbon dioxide (CO2) being stored in geological formations. Saudi Arabia's strategic location and recent policies promote renewable energy and green H2. However, establishing an industrial-scale H2-based economy necessitates a suitable large-scale storage solution. Underground hydrogen storage (UHS) emerges as a prominent option, offering significant storage capacities in the Giga- and Terra-Watt-hour range, effectively addressing seasonal fluctuations in supply and demand from renewables.

Therefore, the present work aims to evaluate the opportunity of UHS in Saudi Arabia and assess potential geological formations (salt caverns, deep saline aquifers, and hydrocarbon reservoirs) and key technical challenges to be addressed for UHS integration in the energy grid. This includes criteria for site selection, storage capacity calculations, and other critical scientific research areas to be studied. The paper reviews the geological settings in Saudi Arabia that are potentially suitable for UHS, Red Sea basins, and sedimentary formations in the eastern basins at the Arabian plate.

The results highlight the requisite fundamental experimental and numerical studies for a complete understanding of H2/brine behavior within formation rocks, including geo-bio-chemical reactions prone to occur during the UHS process. The analysis of H2 thermo-physical suggests a more operational challenge than storing CO2 or natural gas. Commercial demonstration of UHS is crucial, while all the ongoing field tests of UHS (pure H2) worldwide are still in their early stages. Regionally, deep salt caverns and saline aquifers with closed structures or regional seals provide the best structural traps for UHS due to their tight and secure seal system. Down-dip aquifers and sedimentary packages in the eastern basins at the Arabian platform are more attractive and safer options. The discussed analysis of UHS potential in Saudi Arabia sheds light on its integration possibility into the circular carbon economy (CCE) framework to achieve a net-zero emission by 2060.
Process Control Optimization on Water Injection Pump Control Valve to Reduce Energy Consumption and Optimize Waterflood Injection Rate in Gathering Station Facility Pertamina Hulu Rokan
Authors: Prakoso C. B. , Rekayana E. , Susetyo B. , Arifin S. , Zaradan N.
Published: February 2024

A typical Gathering Station Facility in Pertamina Hulu Rokan operates a Water Injection Pump (WIP) to inject produced water back into the reservoir subsurface. Each pump has a pressure control valve (PCV) at the discharge line. The Pump is operated at maximum capacity with an applied single setpoint. A level control valve (LCV) is installed at the return line to maintain the water tank level. This control system configuration when the water supply rate is lower than the discharge pump rate, tends to decrease the water tank level and the control system will respond to this condition by opening the LCV return line, which results in wasted energy due to the water returned to the tank and impacted unstable injection line header pressure. This Process Control Optimization (PCO) provides efficient and reliable WIP system operation by implementing automation of the control valve setpoint adjustment, enabling the WIP to increase or reduce its flow rate based on water tank fluid level (Smart System Control) to eliminate waste energy or reduce return flow when the water supply is lower than pump injection rate, improve pump reliability where the pump is not always operating in maximum capacity and also improving injection rate performance.The method is implemented by applying function logic modification on the Programmable Logic Controller (PLC) and Human Machine Interface (HMI) system which controls WIP operations. The objective is to provide efficient and reliable injection pump system operations, where the WIP flow rate setpoint shall consider tank level, while the control valve in the return line shall have the capability to operate as both level and mainline injection pressure control. The PCO is made to provide a multistage set point that can change automatically, it will change the set point WIP control valve following the operation condition based on the water tank level so that the return control valve will not open immediately when the tank level starts to decline. By implementing the PCO system in two gathering station facilities, the project team has successfully improved the WIP operability and waterflood injection process. The benefit of this system comes from reduced energy efficiency where it was successfully eliminated return flow ~ 13,000 BWPD which equivalent to 13,200 kWh/year, improved 30% stability injection pressure in the header line for supporting water flood / EOR system, decreasing WIP unplanned downtime ~ 50 % and increase injection capacity up to ~ 3000 BWPD which support to mitigate capacity constrain and successfully reactivation oil production wells ~ 70 BOPD.
Successful Deployment of Electro-Mechanical Tractor to Maximize Wellbore Reach in Highly Deviated Wells
Authors: Mashhad H. S. , Jassem H. M.
Published: February 2024

The advancement of drilling technology has made horizontal wells with maximum reservoir contact a possibility. These highly deviated horizontal wells pose huge challenges with respect to wellbore reach during well intervention jobs. The successful implementation of the advanced electro-mechanical tractor to maximize wellbore reach in highly deviated or horizontal wells is presented with the result of several trial test attempts.

The utilization approach of electro-mechanical tractor is based on electro-mechanical drive over hydraulic conveyance approach. Moreover, this advanced fit-for-purpose technology incorporates real-time communication and control while tractoring, including casing collar locator, wheel speed, wheel torque, inclination and relative bearing. Faster operation made possible by the ability of the tractor to move 100 feet per minute. Electro-mechanical tractor was utilized to extend the wireline reach during several well intervention jobs in high inclinations of more than 60 degree.

The several deployments of the advanced electro-mechanical tractor during well intervention jobs in high-angle and extended-reach horizontal wells effectively met the desired objectives and resulted in higher reach along with faster operation. Across several attempts, in which the angles higher than 85 degrees and debris/scale type of restrictions present, the tractor demonstrated an excellent reach result compared to gravity conveyance approach that are limited to 45 to 60 degrees. Moreover, this advanced fit-for-purpose technology surmounted the reach limitations and restrictions, thus unleashed the potential of logging the entirety of target interval to obtain the valuable data for better future decisions.

This paper presents and details the successful deployment of advanced fit-for-purpose technology. Furthermore, electro-mechanical tractor demonstrated its ability to maximize reach in cased hole environment, and provided an economical conveyance solution for logging diagnostic, monitoring, perforating, and mechanical intervention in high- angle and extended-reach horizontal wells.
Advancing Hydrogen Storage in Depleted Gas Reservoirs: A Comprehensive Evaluation of Dominant Trapping Mechanisms
Authors: Alhotan M. M. , Machado M. V. Barbosa , Delshad M. , Sepehrnoori K.
Published: February 2024

The utilization of depleted hydrocarbon reservoirs for Underground Hydrogen Storage (UHS) presents a promising and competitive solution for addressing large-scale hydrogen storage challenges. By repurposing existing infrastructure, UHS can provide a cost-effective and sustainable approach to integrating hydrogen storage within the energy sector. This study aims to identify and quantify the dominant trapping mechanisms that contribute to hydrogen loss during UHS, offering insights for optimizing deployment and ensuring efficient integration into the energy landscape. To achieve this objective, a real-field geological model of a depleted sandstone gas reservoir with a shale cap rock was employed. The Peng Robinson equation of state as well as the viscosity and solubility models were tuned using published hydrogen properties. Recent relative permeability, capillary pressure, and hysteresis data from the literature were also integrated into the simulations to capture the reservoir's dynamic behavior during hydrogen injection, storage, and withdrawal processes. The mechanisms examined include hydrogen residual trapping and hysteresis, diffusion in water and the formation, solubility trapping, geochemical reactions, and the impact of salinity, all of which can influence hydrogen retention and recovery efficiency. The results of this comprehensive analysis revealed that residual trapping was the most dominant mechanism, accounting for majority of the hydrogen loss. This finding emphasizes the need for precise relative permeability data to accurately model and predict reservoir performance during UHS. The geochemical loss was found to be highly dependent on rock composition, with negligible impact in sandstone reservoirs. Furthermore, diffusion in the fluid and the formation contributed to less than 3% of the total hydrogen loss, while the impact of solubility trapping was minimal. This study presents an analysis of dominant trapping mechanisms during Underground Hydrogen Storage in depleted gas reservoirs within a real-field geological model. What differentiates this study is the systematic incorporation of all loss mechanisms using a tunned fluid model, providing engineers with a more holistic understanding of UHS. The findings offer practical insights into how these factors can be optimized for improved hydrogen retention and recovery efficiency. This research is pivotal for engineers seeking data-driven methodologies and best practices in UHS. By delivering actionable knowledge, this study supports the integration of hydrogen storage into the existing hydrocarbon infrastructure, contributing to the development of a sustainable energy sector.
An Improved Method for Oil-Water Contact Determination in Connected Fractured-Caved Reservoir Modeling Restricted by Data of Oil Displacement by Cyclic Water Injection
Authors: Zhang Qi , Li Mengqin , Cao Wen , Niu Ge , Zhang Jing , Wang Qi
Published: February 2024

With complicated accumulation mechanism of fractured-caved carbonate formations, characterization of reservoir and fluid distribution has great uncertainty due to varied oil-water contact and discontinuous reservoir, which brings difficulties to refined reservoir characterization and development index prediction. However, wells are always completed in upper part of the reservoir, instead of drilled through the pay zone, leaving the oil-water contact unknown below the well. It's urgent for a reservoir unit to confirm the oil-water contact. In the study, a method is proposed to constrain the pore volume and aquifer volume in a fractured-caved model based on the projection of water injection data. A material balance equation set of cyclic water injection in the fractured-caved reservoir is used to calculate the total volume of the connected reservoir drained by wells and distinguish the volume proportion of water in the fluid, according to the formation pressure recovery caused by the certain water injection volume in each cycle. A geological model is built via multi-attribute modeling technology and then modified by the outcome of former dynamic reserve evaluation. The seismic attribute threshold of reservoir extraction is controlled by the total reservoir volume, thus the volume of geological model determined. The depth of oil-water contact is adjusted to fit the oil and water volumes related to the water volume ratio, finally a reasonable oil-water contact obtained. Fractured-caved reservoir model and oil-water contact depth are further verified and corrected by drilling and completion data, oil testing and water production data. The feasibility and reliability of the method are demonstrated by a case study in Tarim Oilfield, where the depth of oil-water contact is deduced as −6342m from the first producer in the reservoir unit, and the oil testing of second producer supports it. The method can be applied to single wells or well groups in fractured-caved reservoir that have not yet seen water breakthrough after water injection. It can improve the geological understanding of the reservoir, evaluate the development potential of water injection, and predict the water breakthrough, helpful to the adjustment of development measures.
Fiber Monitoring of TRSSV to Monitor Health and Forecast Failures
Authors: Murdoch E. , Asthana P , Bukhamseen A , Ghamdi T
Published: February 2024

Sub-surface safety valves (SSSV) are critical to the safe functioning of a well. Whilst they are tested regularly, they have limited diagnostics, valves that are experiencing reduced performance are not detected until they fail a test. This typically requires the well to be shut in until remedial action can be undertaken. This paper will set out a new philosophy to use fiber optic sensing to monitor the health of valves and use Artificial Intelligence (AI) to forecast failures and reduce unplanned shut-ins.

Like all machines, failures in SSSV don't just appear. There are typically signs of degrading performance ahead of time. But given the sub-surface location of these valves, it is very hard to detect these signs. In a parallel application, in-well fiber monitoring systems are now deployed routinely for leak detection, flow characterization and many other applications. These fiber monitoring systems can be used to monitor the performance of the SSSV during function testing and establish a health condition of the valve.

This paper will describe the process used to test the concept of monitoring a SSSV using fiber monitoring system first in the work shop. A number of different sized valves will be used. Failure conditions will then be simulated in the test valves and they will be again monitored during function testing in failed condition. This provides a base line to provide indication of SSSV health. The machine learning algorithm will then be trained with these example data. Various coupling methods will be also tested and a final design optimized. The model will then be taken to the field to be trialed in wells that have had fibers pre-installed. Each well will be monitored whilst the SSSV function test was carried out. The results will then be analyzed and a health assessment given. These results will be further fed in to the machine learning model to optimize algorithm. Over time this model will provide a more accurate forecasting of failure and allow better scheduling of workover operations.

This is the first time that a fiber monitoring system has been used to monitor the health condition of a SSSV. This also represents an excellent integration of real time data collection and machine learning interpretation to better schedule workover operations and reduce unplanned shut ins. This safety valve surveillance kit is a strap-on solution for existing hydraulic valves already installed in any wells that have fiber monitoring systems.
Direct CO2 Mineralization Through Foaming Cement and Concrete
Authors: Santra Ashok , Johnson Kenneth , Martinez Roland
Published: February 2024

The use of carbon dioxide (CO2) in the development of products including concrete and oil well cementing is attracting great attention of industry, academia, and government in mitigating climate change. Out of total global energy-related production of ~ 31.5Gt CO2, 8% is by cement production plants. Herein we demonstrate possibility of utilizing a total of 0.378Gt CO2 or 1.2% of total global CO2 by foaming into cement and Concrete. Hydration of Portland cement results in production of 15-20% of Ca(OH)2 (Calcium Hydroxide or Portlandite). All these Calcium Hydroxide can be mineralized into CaCO3 by CO2 foaming. We have developed a proprietary laboratory size blender that can blend CO2 at up to 1000psi. The testing allows us to monitor irreversible conversion of CO2 to CaCO3. We were able to prepare very light weight cement designs by using foamed CO2 technology, with up to 20% enhanced compressive strength compared to commercially available technology without carbonation, such as water extended, and/or silica fume based. Laboratory testing has been performed to optimize the CO2 foaming efficacy and quality. Thermogravimetric analysis has been performed to quantify the percentage of carbonation. Permeability and compressive strength measurement have been performed to ensure that the carbonation does reduce the former and enhance the latter, wherein both changes are improvement towards longer term integrity of cement and concrete. Direct incorporation of CO2 into the matrix of cement and concrete blends reduces the hardening time significantly which is another way of reducing loss of net productive time (NPT) towards sustainability. In addition, it also maximizes the amount of CO2 that can be utilized in this process. The CO2 foaming into cement and concrete is a novel process and have huge potential to directly mineralize large amount of CO2 in useful products.
Prediction of Two-Phase Flow Regimes in Vertical Pipes Using Tree-Based Ensemble Models
Authors: Al-Sharifi H. A. , Alkhudafi A. M. , Al-Gathe A. A. , Baarimah S. O. , Al-Ameri Wahbi , Alyazidi A. T.
Published: February 2024

The multi-phase fluid transfer pattern in vertical flow through pipelines is a significant parameter to be predetermined for predicting the pressure gradient, liquid holdup, and other flow properties. In the present study, the prediction of two-phase flow patterns in vertical pipes using ensemble machine-learning classification models is presented.

For this purpose, ensemble machine learning techniques including boosting, bagging, and random forest have been applied. A decision tree-based classifier is proposed, such as Random trees (RT), J48, reduced-error pruning decision trees (REPT), logistic model trees (LMT), and decision trees with naive Bayes (NBT), to predict flow regimes. Datasets consisting of more than 2250 data points were used to develop the ensemble models. The importance of attributes for different models was investigated based on a dataset consisting of 1088 data points. Feature selection was performed by applying six different optimization methods. For this task, training, and cross-validation were used.

To check the performance of the classifier, a learning curve is used to determine the optimal number of training data points to use. The performance of the algorithm is evaluated based on the metrics of classification accuracy, confusion matrix, precision, recall, F1-score, and the PRC area. The boosting approach and random forest classifiers have higher prediction accuracy compared with the other ensemble methods. AdaBoost, LogitBoost, and MultiBoosting algorithms were applied as boosting approaches. Multiposting has a better performance compared with the other two techniques. The random forests provided a high level of performance. Its average precision, recall, and F1 scores are 0.957, 0.958, and 0.949, respectively. It is concluded that comparing the results of single classifiers, the ensemble algorithm performed better than the single model. As such, the accuracy rate of the prediction of flow regimes can be increased to 96%.

This study presents a robust and improved technique as an alternative method for the prediction of two-phase flow regimes in vertical flow with high accuracy, low effort, and lower costs. The developed models provide satisfactory and adequate results under different conditions.
A Robust New Method for Optimizing Intelligent Reservoir Production
Authors: Chen Cunliang , Han Xiaodong , Wu Qiongyuan , Chen Xiaoming , Liu Bin , Wang Zhiqiang , Sun Shibo
Published: February 2024

With the rapid development of big data and intelligent algorithms, intelligent oil reservoirs production has emerged. It brings new ways to generate profits for oil fields. The key of this technology is related to the rapid processing of oilfield data, which enables to obtain production decisions faster.

This article proposed a new method for intelligent production optimization of oil reservoirs based on big data. Firstly, according to the injection and production development data of the oilfield, a connection model between injection and production wells was established using the principle of material balance. This model not only helps to understand the corresponding relationship between injection and production data in the oilfield, but also enables to predict liquid production. Secondly, a new model was established through reservoir engineering methods which can predict the relationship between oil production and the injection multiples of pore volume, achieving the prediction of oil production in oil fields. Finally, in order to obtain the maximizing net present value, an optimization objective model was established successfully using intelligent algorithms. Compared with the numerical simulation method, this method saved a lot of times and costs.

This method has been using on various types of numerical simulation conceptual models, and the calculation results are perfect consistent with the model results, with an error of only 5%. However, compared to the numerical simulation, it not only saves time and costs, but also improves oil production efficiency.

This method was applied to a certain oilfield in Bohai and achieved excellent results. The results of research have strong promotion significance, which can be spread in more oil fields in Bohai.
Improving Drilling Safety and Efficiency with 100% Reservoir Exposure in a Challenging Low Resistivity Mature Reservoir Associated with Structural and Geological Uncertainties by Integrating Extra Deep Azimuthal Resistivity Technology in a Source-Less Solution - A Case Study From UAE Offshore
Authors: Wahbah Salima , Bellah Samir , Hattori Tadataka , Tsuda Ryuchi , Mumtaz Asim , Sanathoi Potshangbam , Hameed Mahmoud , Rawy Mohammed
Published: February 2024

Improvement in drilling efficiency and maximum reservoir exposure are two key considerations in determining the success of a well. Detailed planning covering these aspects is critical, especially when the reservoir is associated with a complex geological setting. In this case study, oil producers in a complex low resistivity environment associated with high heterogeneity, karstification, caves, collapsed holes, fractured and faulting as common geological features were drilled on the flank of a mature field. Drilling challenges would be profound if the well bore passed through the sub-seismic karst features and the overlaying shale formation. Drilling into such features risk drilling complications that could potentially result in unwanted sidetracks and/or reduce reservoir exposure. The main challenge was to maximize reservoir exposure in the target interval, characterized by thin pay thickness, while maintaining a safety buffer of 15 to 20 ft between the overlying shale and the well trajectory. Maintaining a standoff from an uncertain oil-water contact (OWC) was also critical due to prolonged production in the field.

Historically, a combination of a high-resolution resistivity-imaging service with nuclear magnetic resonance technologies was utilized for drilling the lateral sections in this area, primarily for fluid typing, permeability, porosity distribution, and detailed geological evaluation. However, this solution was insufficient for proactive geosteering to place the wellbore optimally in the reservoir and map the sub-seismic structural changes and the uncertain OWC. To overcome these challenges, Extra Deep Azimuthal Resistivity (EDAR), along with reservoir navigation services was integrated into the existing solution after completing feasibility studies based on the offset data.

The feasibility study demonstrated that EDAR could map the structural and fluid changes from the wellbore satisfying drilling and well placement requirements.

EDAR inversion mapped the structural changes on top of the reservoir, reducing the geological uncertainty related to sub-seismic faults, karsts, and the OWC.

This enabled informed geosteering decisions to achieve 100% reservoir exposure in the optimum target zone and helped to maintain a smooth well profile facilitating a trouble-free completion operation. Placing the well in the best porous zone of the reservoir resulted in a 28% increase in ROP. The completion design was optimized based on fluid distribution analysis and structural information from EDAR inversion. The acquired data improved the knowledge of the geological setting of this area.
Experiment and FEM Modelling of Stress Shadow Effect in Multi-Stage Hydraulic Fracturing to Optimize the Stimulation
Authors: Li Zheng , Wang Jingyi , Gates Ian , Chen Tiange , Zheng Zigang , Lyu Wenfeng , Gao Jian , Yu Hongwei
Published: February 2024

The stress shadow effect is well observed in the field operations of multi-stage hydraulic fracturing and it can greatly influence the fracturing effect. In the research documented here, lab experiments were made with the artificial gelatin blocks to visually examine the stress shadow effect during multi-stage hydraulic fracturing process. A related finite element modelling was conducted to understand the changes of the stress distribution after a first-stage hydraulic fracture evolved. The results of the visual fracturing experiments and finite element modelling (FEM) were consistent, which illustrated that a later-stage hydraulic fracture that follows an previous-stage hydraulic fracture may have its orientation and fracturing pressure altered from that of the previous one due to the altered stress distribution in the formation nearby. The experiment observations clearly showed the process of a first-stage hydraulic fracture generated obliquely at the very beginning due to near-wellbore effect and then turned to extend more and more perpendicularly to the direction of the minimum principal stress. After this first-stage fracturing done, a second-stage fracturing started but the fracture evolved towards a different direction that is nearly orthogonal to the first-stage fracture. According to the related FEM modelling, the main stress shadow affected region was within a range that depends on the injection pressure and the principal stresses difference in the formation nearby. If the later-stage hydraulic fracturing is done beyond this range, the fracture will have a similar orientation and fracturing pressure to the previous one. A suitable spacing between each stage as well as the injection pressure should be well designed to optimize the stimulation.
Carbon Life Cycle Assessment of Non-Metallic Downhole Tubulars
Authors: Sarmah P. , AlAdawy A. , Powell T.
Published: February 2024

Non-metallic oil and gas pipes are replacing their metal alternatives due to their various advantages such as mitigating corrosion issues, lowering total cost of ownership and reducing carbon footprint. Reduction of carbon footprint is an important aspect to consider due to environmental concerns and global initiatives while developing new products. As an effort to assess the impact of utilizing non-metallic tubulars in a downhole environment, this paper explores the carbon life cycle and footprint of metal and non-metallic tubulars.

This paper presents a step-by-step process of the carbon life cycle assessment (LCA) which includes the fabrication of the selected base materials, the loadings, environment conditions, manufacturing techniques used for non-metallic pipe development, logistics and transportation from the manufacturing facility to the destination, deployment and completion in field, as well as end of product life accounting for product disposal and/or recycling. The methodology of evaluating the carbon footprint at each stage is described throughout the composite tubular life cycle. A comparison with metal tubular carbon life cycle is also performed.

An assessment is conducted on the carbon life cycle of non-metallic tubulars starting from base material fabrication, end product development and manufacturing, transportation and logistics, final implementation of the product in the well to the end of lifespan. The study shows a comparison between metal and non-metallic pipes from a carbon life cycle perspective. Various inputs to the methodology (e.g., types of base materials, transportation distance, manufacturing energy input and percentage of recyclable material) are considered, including their impacts on the carbon footprint outcomes.

In this publication, an effort is made to explore the carbon life cycle and footprint of non-metallic pipes focusing on downhole applications. The study shows that non-metallic pipes may provide the potential to reduce carbon emissions with respect to their metal alternatives.
Deep-Learning Based LSTM for Production Data Analysis of Hydraulically Fractured Wells
Authors: Zhang Fengyuan , Xu Minghao , Deng Chao , Zhang Wei , Liu Chuncheng , Rui Zhenhua , Emami-Meybodi Hamid
Published: February 2024

During the production and operations of hydraulically fractured wells, large amounts of data are collected through numerous sensors or flowmeters, which can provide valuable understanding on the formation and hydraulic fractures. Although much studies try to use physical-justification based approaches to analyze these well history data, the analysis accuracy is significantly limited due to many assumptions made in physical models. This paper developed a deep-learning based Long Short-term Memory (LSTM) approach for production data analysis in shale reservoir and proposed a workflow to quantitatively evaluate fracture parameters. The proxy model is based on deep-learning algorithm of LSTM and is combined with a semi-analytical (base) model for multiphase water and hydrocarbon (oil or gas) flow in the hydraulically fractured reservoirs. To rigorously consider the multiphase flow mechanism in the semi-analytical model, LSTM and attention mechanism are introduced to forecast the key relationship of average saturation and pressure for semi-analytical model by training and predicting the time-dependent pressure and saturation series. We generated thousands of numerical simulation cases of wells in hydraulically fractured rservoirs, which provide production data and static reservoir data to train the deep-learning based proxy model. Model verification and comparison show that the proxy model can effectively predict pressure-dependent average saturation relationship with high accuracy. The numerical validation confirms the superiority of the proposed deep-learning based model than the semi-analytical model in accuracy with the error of estimated reservoir and fracture parameters less than 10% and in calculation efficiency with the speed two orders of magnitude faster.
Legacy Wells Screening Method for Potential CO2 Storage Sites
Authors: Enriquez H. Costeno , Dick H. , Holloway C. , Salter R.
Published: February 2024

The authors developed a legacy-wells screening method for potential CO2 storage sites. The screening method enables project teams to evaluate qualitatively, in a consistent manner, the legacy wells risks at potential Carbon Capture and Sequestration (CCS) candidate sites. It does so by identifying the legacy wells current status, preliminary corrective action requirements and associated risks based on a specific data set that can be extracted from public well records.

For CO2 storage sites, legacy wells are existing wells that are located within the predicted CO2 plume and/or pressure front area. When assessing the feasibility of potential storage site candidates, legacy wells risk is an important variable for ranking the feasibility of potential locations against each other. Legacy wells risk is a result of not only the number of wells but also their leakage potential and the complexity of the corrective actions required. Often, only legacy well density (number of wells per squared kilometer) is evaluated, disregarding elements of risk such as well status, well age, well architecture, well mechanical status, etc.; if or when a risk level is assigned to the wells, it is done so in a subjective manner. A systematic method will be illustrated in this paper that evaluates existing well conditions and intervention requirements to evaluate legacy wells risk for potential storage sites.

To evaluate the legacy wells risk beyond only well density and to eliminate the subjectivity of screening, the authors used a method based on a ranking system that considers a few, critical, well characteristics to assign a risk score that can then be compared equally between potential locations. The ranking system assigns risk scores to legacy wells based on the availability and quality of well data, and in parallel the complexity and risks of each potential remediation or corrective action.

The paper will present a case study of a CCS site feasibility study where the workflow was applied to provide a consistent approach to legacy well assessment and qualitative risk evaluation for potential storage sites. Future CCS operators will benefit from this approach to improve decision making before selecting and moving forward with a storage site.
Sustainable Drilling Fluid Design; Utilizing Waste Biomass as Drilling Fluid Additive
Authors: Khan Azam , Shahid Arshad Shehzad Ahmad , Zahoor Muhammad Khurram
Published: February 2024

The use of drilling mud is an essential part of the drilling process in the petroleum sector. It is responsible for managing formation pore pressure as well as cleaning boreholes, among other responsibilities. The necessary qualities can be obtained from the components that are contained in drilling mud. These features can be obtained using specific chemical additions in drilling fluids; however, these compounds can be harmful to the environment and make storage and disposal more difficult. These problems can be alleviated to some extent by using sustainable alternatives to traditional materials. In this study, various solid waste materials were evaluated for their potential use as alternative drilling fluid additives. These materials were assessed for their densities, plastic viscosities, yield points, and gel strengths. There was the possibility of using sustainable additions such as banana peel powder, eggshell powder, date seed powder, and aloe vera gel. The findings demonstrated encouraging outcomes, with noticeable enhancements in comparison to the traditional approaches. Natural solid waste products provide an incremental improvement to already existing drilling muds and have the potential to promote environmental sustainability. By employing waste biomass, our approach improved the quality of drilling fluids while also making them more environmentally friendly. In general, it had a considerable effect in reducing the impact on the environment while maintaining performance.
Automated Workflow to Couple Hydraulic Fracture Modeling Results into Dynamic Simulation Process for Unconventional Reservoir
Authors: Belaifa Elhadi , Abdelrahman Moemen A , Almubarak Abdullah A , Adebamiro Adedayo D
Published: February 2024

The objective of this study is to integrate two main workflows seamlessly; i.e. hydraulic fracture modeling and dynamic reservoir simulation process. A smooth coupling is developed and implemented for unconventional reservoir.

The work is designed as an automated multidisciplinary and integrated workflow consisting of hydraulic fracturing, geologic, and reservoir modeling. The hydraulic fracturing configuration was built at a detailed resolution using a commercial software, which is used to calibrate a 3D subsurface refined geological model using Local Grid Refinement (LGR), and it honors long-term flowback history of unconventional well Pad.

The study was conducted in four main phases Phase-1 is to execute hydraulic fracture modeling where Hydraulic Fracture (HF) job data was analyzed and matched using 3D Mechanical Earth Model (MEM) to predict the HF propagation possible scenarios.

Phase-2 is to transform frac geometry into the dynamic model using LGR methodology. For this phase, it includes a comprehensive software development to automate this transformation process between two different applications. Phase-3 is designed to match the long-term flowback data, where the fracture geometry, such as fracture height, fracture half-length and fracture conductivity used as main history matching parameters.

Finally, for Phase-4, the calibrated model is used to predict the well EUR perform sensitivity analysis.

The implemented integrated workflow helps in optimizing key field development plan parameters, including well spacing, cluster spacing, well stacking, lateral length optimization, testing well interference and its impact on wells’ EUR.
Prospective Saline Aquifer CO2 Storage Resource Estimates in Data Lean Regions
Authors: Gravestock Christopher , Jennings Joseph , Simmons Mike
Published: February 2024

CO2 storage in geological formations is widely agreed to be a key carbon abatement technology. Whilst CO2 can be stored in depleted fields for which there will be abundant subsurface data to calculate storage resource, these calculations will be more difficult for saline aquifers which will often lack data since they may lie outside traditional petroleum systems considerations. Therefore, there is a two-fold challenge: Firstly, to screen for potential saline aquifer storage units rapidly and cost-effectively in any given basin close to point sources of CO2 production.Secondly, for those rock units so identified, to calculate the potential prospective storage resource (PSR) estimate (Mt CO2/km2), both at the gross fairway level and to high-grade areas within the fairway where storage resource is likely to be greatest, or where it meets given thresholds. Such calculations allow potential saline aquifers to be ranked within a region/basin, providing a focus for further data gathering and study.

We have approached this problem by developing workflows for spatial screening that use simple regional geological parameters to identify suitable rock units, and then maximize limited subsurface data to provide an estimate of storage resource. To illustrate this approach, we have used the Cretaceous Shuaiba Formation of the Middle East as an example. The Shuaiba Formation is an established carbonate reservoir in super-giant fields such as Bu Hasa, Shaybah, and Safah (van Buchem et al., 2010; Droste, 2010). It includes bioherm, lagoonal, and more distal facies. Whilst within the industry there is abundant data concerning the Shuaiba Formation, we have limited ourselves to only the data available in the public domain – thus providing a proxy for genuinely data lean rock units. Furthermore, the results, whilst data limited, provide insight into the storage potential of the Shuaiba Formation which is likely to form a key CO2 storage unit in the Middle East.