Logging-While-Drilling (LWD) has incorporated almost all wireline-equivalent technology with the added advantage of logging high-angle and horizontal wells with reduced rig time, critical for cost optimization efforts. LWD measurements are affected by a rugged drilling environment, and logging interpretation with a wireline mindset leads to erroneous results. Identifying measurement artefacts from real formation information is critical for reliable log analysis. This publication discusses the most common effects of drilling dynamics and environments on LWD logs that were observed during logging and drilling wells in cretaceous carbonate reservoirs in an Abu Dhabi onshore field. Log data from more than one hundred wells are reviewed to identify several interesting effects due to bottom-hole-assembly (BHA) design, BHA driving mechanism (Rotary steerable system versus mud motor), tool eccentricity, well angle, mud properties, differential invasion, borehole condition, formation fluid properties and lithology. In a few instances, some of these effects occur simultaneously, complicating the log response. These phenomenons are discussed in detail with actual examples and compared to offset wells and response modellings. The rugged logging environment and limited formation damage due to invasion provide a unique opportunity to obtain additional insight about reservoir behavior, especially when compared to wireline data in an offset well or in the same well. Pre-job planning and modelling can use these phenomena for getting additional information about dynamic reservoir behavior. This paper highlights a few such applications. This paper explains the impact of a dynamic drilling environment on LWD measurements and serves as a ready reference to identify measurement artifacts from real formation information. It is helpful as a guidebook for log analysts, geologist, geo-steering engineers and other non-specialists to identify LWD measurement artefacts.

Challenges associated with volatile oil and gas prices and an enhanced emphasis on a cleaner energy world are pushing the oil and gas industry to re-consider its fundamental existing business-models and establish a long-term, more sustainable vision for the future. That vision needs to be more competitive, innovative, sustainable and profitable. To move along that path the oil and gas industry must proactively embrace the 4th Industrial Revolution (oil and gas 4.0) across every part of its business. This will help to overcome time constraints in the understanding and utilization of the terabytes of data that have been and are continuously being produced. There is a clear need to streamline and enhance the critical decision-making processes to deliver on key value drivers, reducing the cost per barrel, enabling greater efficiencies, enhanced sustainability and more predictable production. Latest advances in software and hardware technologies enabled by virtually unlimited cloud compute and artificial intelligence (AI) capabilities are used to integrate the different petro-technical disciplines that feed into massive reservoir management programs. The presented work in this paper is the foundation of a future ADNOC digital reservoir management system that can power the business for the next several decades. In order to achieve that goal, we are integrating next generation data management systems, reservoir modeling workflows and AI assisted interpretation systems across all domains through the Intelligent Integrated Subsurface Modelling (IISM) program. The IISM is a multi-stage program, aimed at establishing a synergy between all domains including drilling, petrophysics, geology, geophysics, fluid modeling and reservoir engineering. A continuous feedback loop helps identify and deliver optimum solutions across the entire reservoir characterization and management workflow. The intent is to dramatically reduce the turnaround time, improve accuracy and understanding of the reservoir for better and more timely reservoir management decisions. This would ultimately make the management of the resources more efficient, agile and sustainable. Data-driven machine learning (ML) workflows are currently being built across numerous petro-technical domains to enable quicker data processing, interpretation and insights from both structured and unstructured data. Automated quality controls and cross domain integration are integral to the system. This would ensure a better performance and deliver improvements in safety, efficiency and economics. This paper highlights how applying artificial intelligence, automation and cloud computing to complex reservoir management processes can transform a traditionally slow and disconnected set of processes into a near real time, fully integrated, workflow that can optimize efficiency, safety, performance and drive long term sustainability of the resource.

Holistic assessment of project economics and subsurface characterization provides a framework to handle challenging reservoirs. Capturing ranked uncertainties based on their impact on the project and meticulous working towards de-risking the project is key for the success of the entire project. Committing increased production from the field is dependent on proper evaluation of the reservoir. This paper reviews characterization of a tight reservoir deposited in the intra-shelf Bab basin during lower Aptian time. Initial stage reservoir characterization is critical in formulating reservoir development plan and estimating a realistic assessment of rates and volumes for the field. The target formation is a low-permeability (average permeability 0.5 mD) heterogeneous carbonate reservoir sitting directly above and adjacent to a producing carbonate reservoir. It is essential to understand communication between the zones. The pilot well is drilled with 225 ft of conventional core and quad-combo logs. Advanced logs such as resistivity image, cross-dipole acoustic, nuclear magnetic resonance, vertical interference test (VIT), formation pressure (including pressure transient data), and fluid samples were acquired. The main objectives of the evaluation program were to determine the formation pressure, collect representative oil sample(s), conduct vertical interference tests between the sub-zones and collect appropriate data for geomechanical and rock-physics characterization. Thorough pre-job planning and cross-discipline cooperation during the operation provided high fidelity log data and interpretation of the data into a coherent result. This included integration of image data with vertical interference tests from the wireline formation tester (WFT) where barriers were confirmed. In addition, NMR permeability was matched and calibrated using pretest mobility measurements and formation pressure data was combined with full waveform advanced acoustic processing to explain the communication between the upper target zone and the lower producing reservoir. Advanced acoustic analysis helped to fully characterize the target formations with stoneley permeability, azimuthal anisotropy, and presence of fractures. This paper demonstrates the importance of multi-disciplinary team effort in characterization of challenging reservoirs. It highlights the importance of holistic planning before the execution phase, and keeping a focus on the larger goal while executing individual aspect of a complicated project. Formation evaluation measurements have evolved over decades and occasionally it benefits the industry to provide a review of how the latest logging measurements fit together in an integrated manner, for successful evaluation of a challenging reservoir.

Since 2014, ADNOC Onshore has utilized the potential of hoists and commissioned its operational significance, which allowed saving in rig time (4 – 6 rig years per year over 5 years business plan period) and generating a cost saving opportunity. During this period we have faced many challenges and complications mainly during fishing operations which result in unsuccessful retrieval of the completion. Other factors and challenges that are commonly faced which require hoist intervention include: Old wells melted or corroded fish (Tubing + Casing)Reservoir Thammama Zone B wells (High water cut)Pushing the corroded fishComplete plug & abandonPartial plug & abandon required for future side trackWait on conventional rig arrival for intervention Main challenge we faced during our business development phase is losing number of oil producing wells due to fishing complications, therefore the hoist rig is not capable to drill or sidetrack such wells. This will result in delaying requirements to restore production and meet the field quota objective since the wells should be scheduled to conventional Rig intervention. In order to optimize the hoists capability and performance to overcome this issue, we have to optimize based on priority and cost-effective selection criteria which will support to save the rig time & cost. Various advantages of hoists applications experienced in the last 2 years in ADCO include: Running scraperCorrosion and Cement Bond LogsFaster rig move.Work-over well repairs for single completion (well-kill, pulling old completion and running new completion)Well preparation for re-entry and sidetrack plug back to top of 7'’ linerESP work-over. Pulled old ESP pumpsFishing and milling operationsRun 7 "tie back liners.Plug and abandon wells partially or fully Abandonment (inactive string).Spotting and squeezing cement plugs and squeeze off old perforations, changing THS and X-mass tree.Cure Sustainable Annulus Pressure (SAP)Pressure test casingRun completion & special completion such as gas lift mandrels This paper presents methods of optimizing application of hoist in Abu Dhabi onshore fields by modifying enhanced well selection criteria based on the operation experiment and avoid production loss to sustain our field development plan. This implemented strategy benefit the optimization of number of workover wells which will increase in next five years scenarios, which in turn is expected to utilize rig cost savings. In addition, the new selection criteria will create "fit for purpose" solution to overcome these challenges of existing workover wells with less time and complication