Aban Offshore

Abstract With the growing trend of drilling 30,000+ ft horizontal wells from an offshore WHT slot, a new level and specific approach are required to enable successful liner deployment to well TD. This paper describes the well challenges and the use of a casing swivel application in liner deployment that helped complete the longest liner in the deepest drilled well in the Offshore Umm Shaif field, UAE. The recent well design of a 30,000+ ft well rendered the operator's previous approach of using the drill pipe swivel irrelevant. While the market offers casing swivel technology to reduce drag force and aid liner deployment, the optimum intervals where the casing swivel should be placed along the liner must be thoroughly assessed as both compression and tension force acting on each specific placement depth may compromise the casing swivel bearing lifetime and performance. A series of torque and drag simulations were run with a variance of casing swivel placement depth to achieve this optimum value. By optimizing the placement of the casing swivel at 3,485ft below the liner setting sleeve, enabled a large section of the string to be rotated while decoupling torque to be transferred down below the casing swivel. The swiveling effect resulting in axial frictional drag reduction, alleviates buckling risks and provides more weight at the surface to push the liner to TD. In this case, the collaboration between the operator and technology provider yielded a successful deployment of 17,678 ft of 6-5/8" liner on a 30,000 ft MD horizontal well. The liner was stalled and could not be deployed under the conventional deployment at 28,100 ft MD due to drag and buckling events. After attempting to wash down without any progression, rotation was then initiated with the help of the casing swivel at 20 RPM and 4 BPM circulating rate, which successfully completed the existing stand. Subsequently, the rotation continued for the last 1,892ft at a controlled tripping speed where it finally landed at well TD. The casing swivel saved approximately 5 days of rig time, avoided NPT and completed the jobs efficiently and safely. It also enabled the operator to complete a long lateral section, maximizing and extending beyond the boundaries of typical offshore wells. Proper placement of the casing swivel technology enabled the liner string to be deployed in the challenging offshore jack-up rigs, increasing the success rate of liner deployment, and saving overall cost and time, avoiding the need to POOH the failed liner string and run an additional wiper trip.

The global transition to renewable energy is essential for addressing growing electricity demand, reducing greenhouse gas emissions, and combating climate change. ADNOC is committed to this shift through its 2030 Sustainability Strategy, which aims to cut GHG emissions intensity by 25% by 2030, requiring innovative technologies and solutions to meet this goal. This project proposes constructing a hydroelectric plant on Zirku Island, utilizing the cooling water return channel to the sea. The approach is to install an in-line turbine within the cooling water return pipeline, driven by the flow of seawater, to generate electricity. The electricity produced will be fed into the grid to meet the island’s energy demand, simultaneously allowing more fuel gas to be redirected to downstream markets. The cooling water network services all consumers within the process plant and eventually returns water to the sea through a degassing tank, adhering to strict environmental standards. The existing system operates with a flow rate of 9,000 cubic meters per hour of treated seawater through a 48-inch pipe, maintaining a minimum pressure of 25 PSIG. Initial studies suggest that this setup could generate approximately 3,206 MWh of electric energy annually. The estimated project capital expenditure (CAPEX) is around 573,500 USD. Further detailed studies are underway to assess the most suitable turbine type and explore potential system modifications for enhancing efficiency. This paper presents a technical proposal that illustrates how waste energy can be converted into clean, renewable electricity, providing a reliable energy supply while supporting ADNOC’s sustainability goals and contributing to the UAE’s broader renewable energy objectives. Importantly, this innovative use of hydropower technology could serve as a model for other offshore oil and gas sites globally, demonstrating how wasted potential energy can be repurposed into green energy and inspiring similar initiatives.

Abstract This study aims to enhance predictive accuracy in dynamic reservoir modeling through geological integration of static model and field historical data. It specifically focuses on horizontal permeability enhancement, targeting better alignment with production history. Utilizing a combined approach of geological concept application and data analysis, this study conducted core and thin section observations from 39 wells, in addition to image log data analyses from 8 wells. The study identified and classified geological non-matrix features (dissolution vugs, various types of fractures) that influence fluid flow, examining their correlations and trends with reservoir properties such as rock type, porosity and permeability. The comprehensive analysis led to the successful delivery of geologically reasonable horizontal and vertical permeability models that align with historical dynamic data. Through detailed observations and classifications of the geological non-matrix features which contribute significantly to the fluid flow within the reservoir, the study highlighted the discrepancies between matrix permeability and well test permeability. This discrepancy primarily stems from the different measurement scales and the non-consideration of significant geological features in the static model. Certain static rock types were found to be predominantly vuggy and micro-fractured, which required targeted permeability enhancement. Additionally, long planar fractures were found to develop in areas with low porosity, indicating that modeling of these features in such areas aligns with field history and improves model accuracy. These findings not only challenge existing methodologies but also propose a more integrated and geologically reasonable approach to reservoir modeling. This study introduces innovative methodologies for incorporating geological concepts into reservoir modelling, particularly in the interpolation of static and dynamic data to enhance prediction accuracy. Our findings provide new insights into the integration of geological features with reservoir properties, offering significant implications for improved reservoir management and recovery strategies in the petroleum industry.

The effective operation of water injection pumps is vital for enhancing oil recovery in the oil and gas industry. To ensure optimal pump performance and prevent unplanned downtime, this study focused on implementing predictive maintenance strategies. We began by identifying five critical operational parameters-Seal Pressure 1, Seal Pressure 2, Vibration Data for the Drive End (VIB DE), Vibration Data for the Non-Drive End (VIB NDE), and Ampere. These parameters were monitored and analyzed to evaluate their impact on pump performance and maintenance needs. To achieve this, we applied three machine learning algorithms: Extreme Gradient Boosting (XGBoost), Light Gradient-Boosting Machine (LGBM), and Random Forest. Each algorithm was independently trained and tested on the dataset corresponding to each operational parameter. We assessed their performance using key accuracy metrics, including R squared, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). Following this, we developed an Ensemble model, combining the predictive outputs of XGBoost, LGBM, and Random Forest. The Ensemble model was then applied to the same parameters to evaluate its ability to address the limitations observed in standalone models. The results demonstrated that the Ensemble model consistently delivered superior performance, achieving lower RMSE and MAE values and higher R squared coefficients across all parameters. This study culminates in the validation of the Ensemble model as a robust and reliable approach for predictive maintenance. By leveraging the strengths of multiple algorithms, the Ensemble model offers significant improvements in accuracy and reliability, contributing to more effective maintenance systems for the oil and gas industry.

Abstract This paper outlines a comprehensive methodology to tackle challenging operation of drilling 12-1/4" hole section in one of the offshore field Abu Dhabi. This hole section is highly prone to various problems where significant Non-Productive Time (NPT) and Invisible Lost Time (ILT) have been recorded. Thus, the drilling team is seeking for a novel fit-for-purpose approach to deliver operational excellence systematically through continuous performance improvement. Drilling performance support group assist drilling engineering team by providing an integrated real-tome operation monitoring, reporting, and advanced BHA simulation capabilities. Initially the problem was identified as high BHA failure rate caused by varying vibration modes coupled with hole cleaning and wellbore instability. BHA simulation and Geomechanics modelling were then performed on past wells to identify the root causes of each failure event. These analyses leverage High Frequency (HF) operation data recorded through Real-Time function. Performance reporting is then presented through interactive dashboards accessible by all drilling team members. These steps are performed with dedicated tools to improve the team's efficiency while simultaneously reduce gross errors. The methodology was first implemented back in 2020 with real-time monitoring and reporting functions. BHA simulation and geomechanics modelling capability were included in 2021. The simulation provided the most optimum BHA stabilization configurations for each well profile. Geomechanics study allowed a calibration on Mud Weight and bridging material properties to limit borehole collapse and assist in cuttings evacuation. The full implementation has improved the performance through 14% reduction in ILT, 80% reduction in hole problem and stuck pipe cases, and 64% reduction in BHA failure rate, allowing the team to deliver more well based on annual target. The promising results indicated by the ILT and NPT figures allowed the operator to extend the 12-1/4" envelope further, which already captured in future well plans. This methodology has brought a greater technical understanding for the drilling team to deliver overall improvement in 12-1/4" hole section. A dedicated performance groups allows the provision of effective support for drilling engineering and operation teams. This approach allows each team to focus on their primary objective in parallel.