bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving Operations Within Capital Project Execution with Case Examples
Authors: Shenoy Ramachandra , Haley Kerry
Published: November 2020

Recent surveys of major capital project performance conclude that most oil & gas major capital projects fail to meet their budget and schedule objectives. We describe a new technical framework for project execution, drawing upon principles originally applied in the fields of computer and telecommunications network systems design. The constraints and activity synchronization needed to successfully operate digital network systems have many similarities with, and arguably much greater complexity than, the constraints and activity synchronization required to seamlessly execute capital projects. We show the applicability of utilizing network engineering principles to improve capital project execution. The observation is not new – indeed other industries routinely apply network systems engineering to manage their complex project operations and associated supply networks. Companies successfully applying such principles include Amazon, Federal Express and Walmart.

After giving a high-level introduction to the commonality between the fields of network systems engineering and project management and execution, we briefly compare our approach with related ones such as Lean Project Management. The latter approach draws from the operations research and industrial engineering fields, which are foundational in network and systems engineering. We close by describing case examples from recent oil & gas major capital projects and the superior performance obtained by using a network systems approach.
Artificial Intelligence Aims to Save Lives in Offshore Marine Vessels
Authors: Almadhoun Wael , Al-Shimmari Nasser , AL-Qamzi Abdulla , Al Owaid Hatim , Al-Shamsi Ali , Al-Naqbi Maha , Ateya Ali
Published: November 2020

In ADNOC Oil and Gas 4.0 mission, we are committed to empower people with the needed capabilities and Artificial Intelligence (AI) technologies to fuel innovation, efficiency and more importantly achieve and sustain a 100% HSE, by transforming the way of handling HSE events by moving from reactive to proactive approach. The ultimate objective is to save lives, empower the vessel Captains to immediately identify and respond to violators, improve the HSE culture of the crew, and automatically generate live data analytics and statistics with the aim of improving safety in operations. The implemented AI use cases are; deviation for not wearing Protective Safety equipment in designated areas, violation of not utilizing safety passages, alert when no watchman in muster station, alarm when man overboard incident, alarm when man fell on stairs, and live Personnel on board each weather-deck. When introduced the Artificial Intelligence cameras, our marine vessels will adopt a smarter automated response and reporting culture, which will in turn, lead to increased safety oversight of our critical offshore operations. Therefore, with the advent of the AI technology, many common business processes have been automated thus enabling personnel to increase their focus on more important tasks while technologies like the AI System can handle many of the time consuming tasks.

The solution components consists of Artificial Intelligence platform, high definition cameras, local server, wide-range WiFi access point, network infrastructure and a tablet. On the tablet device, the captain have full coverage of the vessel weather decks, working areas and restricted zones with a feature to generate alerts when detecting an emergency situation. This was provided to empower the vessel Captain to acknowledge and respond to violations as well as take a proactive action to prevent incidents from happening. The Machine Learning algorithm has been trained on actual scenarios and will be continuously improved by adding more recorded event to retrain the initial model. Currently, the prediction model is performing on the vessel operation mode and recording events with high rate of accuracy. In case of automatically detecting an alerting or non-compliance event, the captain would be notified, beacon lights and sound, and log recorded in the local and central system with a photo and a short video clip of the incident. The process of identifying HSE deviations are becoming digitally transformed by deploying AI capabilities on real-time video streams. The AI-based camera system leverages Computer Vision features that enables machines to get and analyze visual information and take action. The whole process of identifying HSE violation events has been digitally transformed by deploying an artificial intelligence solution to perform real time video analytics.
Miscibility Tracking in Reservoirs with Large Compositional Variation Undergoing Miscible Gas Injection
Authors: Mogensen Kristian , Ali Ahmed Elsayed
Published: November 2020

Miscible gas injection is a proven enhanced oil recovery method for medium-light oils. Miscibility is typically assessed with the slimtube experiment, which aims at identifying the minimum pressure (MMP) above which the displacement process is multi-contact miscible and leads to low microscopic residual oil saturation. During implementation of a miscible gas injection scheme, there will often be areas close to producing wells where the reservoir pressure is below the MMP and the question then arises whether the process can still be considered miscible. Another complicating factor occurs in reservoirs with significant lateral fluid property variation, where it is not intuitively clear how the MMP varies aerially.

We employ compositional reservoir simulation to investigate the impact of flowing bottom-hole pressures below MMP on the development and propagation of a miscible front. Starting with 1D simulations, we track a number of important properties such as the effluent gas composition over time, the component K-values at distinct positions along the displacement front, as well as the pressure at the front over time.

Due to the high gas mobility, the pressure drop per unit distance is greatly reduced in the areas flooded by gas. This means that the reservoir pressure at the gas-oil front is higher than the pressure at the same position before arrival of the front. Therefore, a miscible displacement can be maintained even when not only the flowing bottom-hole pressure but also the average reservoir pressure is below MMP. A key requirement is, of course, that the gas is injected at a pressure above MMP. We evaluate various parameters in terms of their ability to distinguish between miscible and immiscible displacement and find that the phase density difference versus pressure provides a unique advantage for estimating the MMP and we believe it can be used not only in 1D slimtube simulations but also in other thermodynamics-based algorithms. We also find that the vapor mole fraction, inferred from GOR measurements, is a better metric than GOR itself and that molar ratios applied to the effluent gas are very useful for tracking miscibility.
Novel Approach to Link Petrophysical Groups into Electrofacies by using NMR Logs
Authors: Celma R.. , Farooq U.. , Douik H.. , Alawadhi A.. , Saputelli L..
Published: November 2020

Petrophysical Groups (PG) from cores and log facies (electrofacies) are two of the main outputs generated in the petrophysical domain. Those are particularly contributors to the highest degree of uncertainty during the reservoir modeling, with the subsequent high-impact in field development decisions. Detailed core analysis is the preferred main source of information to condition the PG, however, since there are generally more un-cored than cored wells, logs are the most frequently applied source of information to extrapolate petrophysical groups by the use of log facies. The approach of this investigation is to apply machine learning to move from the core domain to the log domain and to determine relationships to generate properties for the three-dimensional reservoir model.

All wells have a full set of logs (Gamma Ray, Resistivity, Density, PEF and Neutron) and few have routine core analysis (Permeability, Porosity and MICP). On a first pass, logs from selected wells are classified into Self Organizing Maps (SOM) without analytical supervision. The idea of this step is to observe the capability of the log data to self-classify according to the log response. In a second stage, core data is used to define petrophysical groups (PG) by clustering the data in into similar pore throats from the MICP and permeability vs. porosity relationships, also thin section were used to introduce geological meaning to the to the PG. The PG are linked to the NMR pore-size distribution (Invasion correction were applied in order to observe only the pore geometry content on the T2 distribution) by correlating into a pre-determined standard NMR pore geometry distribution, the result is that each PG group has a particular T2 range and proportion. In the next step a pseudo NMR curve is create by the use of a Neural Network constrained by the range and proportions obtained and observed in cored wells. This pseudo NMR can be generated in all wells (even the ones Un-cored or without NMR) and generate PG groups at log scale hence the PG logs are controlled by the relationship between core (Pore throat, permeability, porosity and Geological Facies) and pore-size distribution coming from the NMR Log.

The result is a robust model capable to capture the core relationships and able to predict properties preserving the geological features of the reservoir. The application of this method makes possible to determine the minimum and most relevant source of data to address the issues caused by the heterogeneity of the rock. The applied workflows also show how to break the autocorrelation of variables and maximize the usage of logs.

This work demonstrates that the introduced data-driven methods are useful for rock typing determination and address several of the challenges related to core to log properties derivation.
Evaluating and Optimizing A Program to Reactivate Water Injectors in A Mature Field by Integrating Conventional Physics with Artificial Intelligence
Authors: Calad Serrano Carlos Mario , Gutierrez Fernando , Sarma Pallav
Published: November 2020

The application of a novel data and physics driven modeling technique integrating many data sources such as historical production and injection data, wellbore andcompletions data for a mature waterflood in the Cuyo basin in Argentina is presented. This innovative technology combines the benefits of speed of machine learning with the predictivity capabilities of traditional simulation. The initial objective was to identify opportunities for optimization of ongoingsecondary recovery projects to increase production and reduce costs in the subject field. During the execution of the project the need to evaluatereactivation of inactive injectors was identified and the software was modified to include this feature.

The technology integrates machine learning techniques with partial differential equations of fluid flow such as thoseapplied in conventional reservoirs simulation models. Because the presented approach honors reservoir physics, it provides long term predictivecapacity and always ensures physically realistic solutions. The technique is inherently low order and continuous scale, and therefore orders of magnitude fasterthan traditional approaches.The approach is probabilistic in nature, allowing for quantification of uncertainty. Given the complex conditions of operation and control in secondaryrecovery projects, and sparse and noisy data, it is not feasible to define a unique deterministic solution. Therefore, the proposedapproach providesphysically and statistically possible distributions (ranges and frequencies) of the variables affecting reservoir behavior.

One of the features developed for this project is the ability to "reactivate" injectors and model the response of thefield with these injectors operating at an optimum level. This feature was used to evaluate the reactivation of 12 inactive injectors. The tool delivered theoptimum number of injectors to be reactivated, the optimum volume to be injected at each injector and the order in which the reactivation would bringthe largest/quickest value. The results were compared with the optimisation plan obtained by redistributing water without the injectors and the best NPVsolution chosen.At this time the operator has not implemented the plan due to market conditions.
A Novel Well Design, Completion and Testing Strategy in a Changing Fluid Distribution of an Appraisal Well
Authors: Aftab Muhammad , Swain Ashis , Sultan Mir , Al Blooshi Abdulla , Al Shamsi Mohamed , Mingsheng LV , Abu Snaineh Bashar , Al Mansoori Sara
Published: November 2020

Generally, appraisal wells are drilled to reduce uncertainty. However, occasionally reserves uncertainties may increase in a heterogeneous carbonate reservoirs specially challenging stratigraphic limit of reservoir facies. Under such circumstance, sometime operators rethink of further investment in the field development when in-place volumes are marginal.

The objective of the study is to present how we achieved well design modification and test strategy in a dynamic environment. Optimal well test design, execution and analysis can help mitigate major uncertainties, which were not considered during initial planning phase

The subject appraisal well was drilled as a vertical hole in an up dip direction to the first appraisal well. However, Open Hole (OH) and mud log data indicated the reservoir to be tight and in some portion dominated by water flow during sampling even though clear hydrocarbon presence observed in core chips and cuttings analysis. After detailed studies of the available data, a decision was taken to horizontalize the well towards first appraisal well. While drilling, geological barriers were encountered as indicated by the presence of different fluids in the horizontal section. Variable fluid presence (water and oil) posed a challenge with respect to well completion and testing. This paper describes the process of completing the well in an evolving complicating situation and how successful well test design and execution helped to mitigate the uncertainties.

OH Logs, Wire Line Formation Tester (WFT) and test data from the studied and existing wells in the area were used to design the well test and interference with first appraisal well in an evolving situation, which is not typically faced in well operations. Hence, the results obtained provide an additional information that helped to conclude variable fluid distribution and its dynamic connectivity to the first appraisal well.

Well was completed followed by test as designed and Production Logging Testing (PLT) was conducted to define reservoir contribution. Post well test analysis and comparison with existing WFT and test data from existing well helped to conclude results and address the uncertainties.

This paper summarizes the design process, challenges faced in an unexpected variable fluid distribution in the horizontal section and accordingly how well test analysis was performed to conclude the results that helped to take optimal investment decision for the development of this marginal reservoir.
Face the Challenge to Reap the Benefits Automation and Smart Technology
Authors: Thonthe chettiar Tharmalingam , El-Sawah Mohamed , Almentheri Ibtihaj
Published: November 2020

In the current time of uncertainty, Oil & Gas Industries need to manage the cost, extract the most value from current assets and sustain its production. Automation and smart technologies are key enablers to fulfill such objectives. Current era of digital world, automation is a major driver in Oil and Gas industry today. Digitalization, automation and deployment of smart technologies, improves the plant availability and provides plant information, equipment conditions at fingertips of engineering, operation / maintenance team to troubleshoot for the improved plant performance. Availability of such information at desired location facilitates early decision and supports in attaining an operational excellence.

Deployment of ‘Digital Oil Field’ concept is a key enabler to manage the plant operation effectively from centralized remote location. It supports 100% HSE with minimized exposure of hazard to the work force. Automation introduces a ‘single window’ operation for an efficient management of plant operation and supports predictive / preventive maintenance to ensure plant availability with no production loss. Deployment and realizing the benefits offered by automation and smart technologies are not without challenge. We face challenges at every stage of deployment, right from selection of technology, building infrastructure, lack of skilled manpower to handle the new technologies, multiple systems interfaces, abundant data, alarm flooding, cyber compliance etc.,. In order to seize the full potential benefits of "automation and smart technology, each challenge needs to be turned in to an opportunity.
Chemical Sand Consolidation as an Effective Alternative to Conventional Sand Control Methods in Ecuador
Authors: Izurieta Alvaro , Serrano Fabrizio , Andrade Patricio , Burgos Angel , Rodriguez Ricardo , Jaramillo Jose
Published: November 2020

This paper shows the results from chemical sand consolidation treatments used in the M1 sandstone as the main sand control method. For a successful implementation of this technique a workflow that combines field data, temperature modeling, laboratory analysis, petrophysics and geomechanics has been developed. Production results reports zero to near zero sand production with almost no impact on well productivity.

Pre job design steps used to secure a consolidated reservoir after the treatment are described. Temperature is a key parameter to model since the resin is temperature activated. Laboratory tests and simulated temperature defines the curing time. A step rate test is used to calculate the injectivity index and evaluate the need for an acid stimulation treatment before the consolidation system is pumped into the well. This test is repeated after curing time to evaluate any possible impact on productivity. Determination of the Unconfined Compressive Strength (UCS) of the consolidation sand and critical sand production rate are also included in the analysis to understand sand production potential in the field.

Chemical sand consolidation consists of two main components, resin and hardener. The consolidation fluid along with a pre-flush and an over-flush have typically been pumped into the well using production tubing. This sand control method has been proven to be relatively low in cost compared to other sand control techniques and the treatment can be performed in a relatively short period of time. These two characteristics and the positive production results observed thus far makes this technique attractive for upcoming sand control completions with unconsolidated reservoirs with similar characteristics to the M1 sandstone.

In addition, conventional sand control methods rely on a particle size distribution (PSD) from a representative core sample for a successful implementation whereas chemical sand consolidation system is PDS independent.
Ground Robotics: The Route to Intelligent and Reliable Operation & Maintenance
Authors: Duco Drenth , Matthias Biegl
Published: November 2020

This paper identifies the interdependency and impact of the maintenance of assets with the use of robotics in combination with artificial intelligence to support the modern ‘Operator 4.0’. The execution of high-quality, well-planned and efficiently-executed maintenance is crucial in today's energy production process, both from a reliability/ functionality and from an economic point of view. Applying such smart maintenance is an important driver to create long-lasting reliable performance during the operational lifetime of an asset, which will also be extended by executing such intelligent maintenance.

Since a few years, a number of Robotics and Big Data technologies have come to the market and these are two of the major market disruptors, accelerating innovation and noteworthy changes to the industry. Well-equipped ground robots will become the new data gatherers, using a suite of high-quality sensors and predictive algorithms to provide real-time advice. Interpreted by experienced maintenance engineers - this leads to intelligent decision-making to sustain or enhance high performance levels on any production site. Important breakthrough of this development is the strong reduction in cost, the ‘simplicity’ and the almost miniatured size of the associated equipment, and the acceleration in e.g. computing power to process the many data streams and convert it in easy to interprete information.

We have assessed, in practice, how such robots can indeed act as the (extra) eyes, ears and brains on the ground, for today's - and tomorrow's - operator and/or maintenance technician. This paper will detail a number of examples of state-of-the-art robotic solutions for operation and maintenance purposes, coupled to Big Data technologies, and the challenges that lie ahead of the industry to create the high-capital industrial installations of the future, starting today. The information gathered during our demonstrations and described in this paper will lead to new, inspiring and smart ways of designing, operating and maintaining energy production infrastructures - brownfield and greenfield, onshore & offshore - by using ground robots and the latest sensor and predictive maintenance technologies, adapted to the workforce of the 21st century.
Drilling Real-Time Data: Data Acquisition Time Synchronization Framework for Critical IR 4.0 Solutions
Authors: Alotaibi Bader , Contreras Otalvora William , Alzahrani Majed
Published: November 2020

In recent years, oil and gas Drilling and Workover (D&WO) operations have grown significantly and as a result produced huge amount of data. Today, modern rigs transmits more than 80,000 real-time data points every day. The quality of the generated data is directly proportional to the value it can provide in predicting drilling issues and discovering hidden knowledge. One of the challenges with this high frequency overwhelming amount of data is the concept of time.

Data providers in a single site may have different time references. As every data point is stamped with the time of the computer running the data generation software, having different reference to the time makes it impossible to integrate the different types of data being generated. Additionally, it significantly affects the accuracy of critical Internet of Things (IoT) and machine learning models that rely on precise timestamps within a narrow window for detection, alerts and action.

In this paper, a full framework is introduced to address the time synchronization challenge using the industrial standard and adopting Wellsite Information Transfer Specification Markup Language (WITSML). The framework tackles the problem using three integrated steps. The first step is identifying time drift from each data source. The second step is fixing the time drift by intelligently correcting the data based on trends of the drift. The final step is deploying an IoT device to ensure GPS level time. The paper will demonstrate how such a framework can help in detecting potential satellite communication failures.

The solution improves drilling data quality and provides accurate early warning signs of operational issues. Additionally, it enables the use of fully synchronized real-time data sources to perform analytics and engineering calculations to further advance drilling automation.
Long-Term Inflow Profile Monitoring with Markers in Horizontal Gas Wells with Multistage Hydraulic Fracturing
Authors: Katashov Alexander , Ovchinnikov Kirill , Belova Anna , Husein Nadir , Buyanov Anton , Suprankov Kirill
Published: November 2020

Traditional methods of inflow profile monitoring are not always effective, especially when tight reservoirs are considered. One of the most progressive solutions is the use of marker technologies based on the markers' selection and subsequent identification in fluid taken at wellhead [1]. The main advantage of this technology is that there is no need to suspend work for hoisting operations in order to obtain informative field-geophysical data during well operation. The main subject of work is a fractured gas well with pumped marked quartz polymer-coated sand.
Adaptive Framework for Resilient Supply Chain Using 3D Printing in Oil and Gas Industry
Authors: Al Tartoor Yousef , Khalaf Adel , Awadallah Mohammed
Published: November 2020

Resilient supply chain management plays an essential role in the success of organizations in terms of operational performance, efficiency, and sustainability that in turn ensures business continuity. While effective supply chain is directly dependent on logistics, inventory control, and materials handling, it is also strongly interlinked with the utilization of new technologies that will enhance the complete supply chain cycle. This paper develops a framework that introduces three-dimensional (3D) printing in the oil and gas industry, taking into consideration the challenges that this technology is facing to penetrate the conservative oil and gas industry and realizing its potential benefits to the business.

This research work utilizes different purchasing models to cover a significant category of expenditures in an oil and gas company, which is providing an alternative cost effective option for sourcing high value and long lead old/obsolete spare parts from original equipment manufaturers (OEM)s overseas. Several frameworks used worldwide were employed, such as the Kraljic matrix & PESTLE (Political, Economic, Sociological, Technological, Legal and Environmental) analysis, to employ different manufacturing/supply technologies for different stock item classes. These tools provided a systematic pathway to perform market analysis of the existing local 3D printing market and potential for growth and competitiveness in upcoming years. This paper also presents a trial attempt to 3D scan and digitize 215 materials as a first step in the prepared framework guideline. This study works in line with recent ADNOC initiatives in promoting local workshops and In-Country Value (ICV), andUAE precautions taken to mitigate the impact of the COVID-19 pandemic in oil and gas plants.

The adaptive framework provided a roadmap to debottleneck the constraints that conventional supply chains faces with the critical supplies. The developed decision support matrices, employing semi-quantitave approaches, serves in achieving the business need of every supply in terms of cost, schedule, or combination of both. The framework provides a guideline on the utilization of 3D printing, while maintaining the highest levels of quality. A qualitative analysis showed that the introduction of 3D printing would increase the diversity and market competition leading to potential price reduction.

The utilization of 3D printing technology as part of a strategic supply chain process is not well developed. This study presents an effective framework that will increase the confidence level of oil and gas operators in utilizing this technology and benefit from its values.
Tubing Straddle System to Restores Oil Production Using Digital Slickline Conveyance A Case Study
Authors: Gilani Syed Zubair , Alfadhli Wuroud Mohammed , Kurma Ravi , Al-Mansour Yousef , Al-Sulaili Mousa , AL-Habib Amal , Al-Qaheem Sara , Al-Menai Deema , Karam Eynas , Al-Hamad Hazza , Al-Shuaib Abdulrahman , Fituri Mohamed Aiman , Ayyad Hazim , Mosbah Mohamed , Al-Hajji Ahmad , Ikhsanov Meirbek , Abdulrahim Khaled
Published: November 2020

The mature Great Burgan field comprises of more than 2000 wells to date, many of these wells utilize artificial lift in their production to maintain production targets. Tubing leaks and integrity issues pose major challenge to the artificial lift pump; these leaks eventually cause pumps temperatures to exceed the operating limit, trip and stop production.

The waiting time for a workover rig is about 4 months, this converts to a significant loss of oil production in every well with tubing integrity issue.

To reach and sustain the production target, rigless tubing repair is perceived as a viable quick solution to maintain production until workover rig becomes available.
Casting Requirements of Super Duplex Stainless Steel Products – Lesson Learned from a Failure Case Perspective
Authors: Anghel Gelu Dragos , Nallamothu Narayana Swami , Singh Harendra , Kamal Faris Ragheb , Takieddine Oussama Halim
Published: November 2020

Excellent mechanical properties and superior corrosion resistance in aggressive environments, recommends Super Duplex Stainless Steel (SDSS), for specific Oil & Gas applications requiring a high reliability and integrity of equipment. Generally, SDSS would be a solution for systems handling oxygen free or deoxygenated fluids with a relative high content of chlorides, such sea water or, with precautions, even well fluids.

If exposed to sour service, additional precautions must to be taken for this class of materials in order to avoid occurance of cracking mechanisms associated with hydrogen sulfide presence and to comply with environmental and material limitations imposed by NACE standard MR 0175/ ISO15156.

Despite of meeting material selection criteria, pumps faced major fabrication challenges and quality control issues subsequentlly reflected through a premature failure of equipment; generated by concomitent interaction of inappropriate fabrication aspects, including the pouring, quenching and welding of SDSS material.

Specifically, quality control is a critical factor during fabrication to avoid unexpected in-service failures, involving major operational issues and unforeseen expenses.

This paper aims to discuss SDSS casting issues encountered during fabrication of pump casings, from a failure case perspective, providing an optimized approach for successful completion of cast manufacturing process.
High Resolution Fracture Analyses and 3d DMX DFN Modeling of Triassic Dolomites; Wadi Bih, Ras Al Khaimah UAE
Authors: van Dijk Janpieter , Lazzar Raffik
Published: November 2020

The present paper regards a high-resolution 3d fracture DMX modelling exercise applied to Triassic dolomites of the Ghail Fm, outcropping along Wadi Bih in the territory of Ras Al-Khaimah (UAE). The outcropping rocks show a low primary porosity, are well bedded and highly fractured (jointed) up to cm scale. They are an equivalent of the hydrocarbon producing Khuff Fm in the subsurface, and as such the exersice shows the relevance of applying new technologies to outcrop observations to confront with subsurface situations. Secondly, the exersize shows several new unique elements and related technologies not presented previously. The workflow presented which allows to arrive from observations to a 3d data driven fracture model, applying new technologies and algorithms using specific modules of the DMX protocol.

Data collected comprise direct hand measurements of fractures and bedding planes, and 3d calibrated HR photographs. The scale of the model ranges from cm to meter scale fractures (core to borehole image scale). The parameters that have been analysed are size (length, height), orientation (set recognition), truncation relationships (BIXTV) between fractures and bedding planes, and spatial distribution (spacing) of the single fracture sets. The analyses and confrontation between the bedding tilt and the orientation of the 5 recognised fracture sets demonstrates that the fracture network is passively tilted with the bedding plane. A methodology is presented to arrive from in principle 1d (lineament) observations upon 2d sections (bedding planes surfaces and vertical sections) to statistical models and the usage in 3d fracture modeling.

The resulting 3d model is generated as a Data Driven Model using the DMX protocol, which is directly connected to the observed features which are themselves present in the model, and comprises 5 sets with the following parameters reflecting the observed mathematical models: Specific spatial spacing relationships, size distributions (lengths and heights), relationships with modelled bedding plane surfaces, undulation of fractures, and 3d spatial truncations (XTV) between fractures and between fractures and bedding planes. This model is interrogated for 3d connectivity in different directions, P32 density (related to fracture porosity) and can be confronted with subsurface datasets from (preferably oriented) cores.

The example shows for the first time how relatively simple and straightforward observations, which can be collected by hand, or with 3d stereofotogrammetrical techniques or drone technologies, can be used to build 3d analogue models that accurately mimic geological relationships.
Using Sequence Stratigraphy to Resolve Depositional Misconceptions on the Arabian Plate – The Example of the Gotnia Basin Creation and Infill
Authors: Gravestock Christopher , Van Buchem Frans , Simmons Mike , Davies Roger
Published: November 2020

The Jurassic stratigraphy of the Middle East includes the world's most economically significant petroleum systems, containing multiple world-class source, reservoir and seal packages. Yet in a regional context, these depositional systems are still not fully understood, leading to inconsistencies in lithostratigraphic nomenclature across international boundaries and misconceptions in the stratigraphic architecture limiting exploration and production success. We have applied sequence stratigraphic principles across the Jurassic strata of the eastern Arabian Plate to increase stratigraphic understanding and resolve some of the common misconceptions. This provides a robust age-based framework to reduce lithostratigraphic uncertainty across international boundaries and provides predictive capabilities into the temporal and spatial distribution of source, reservoir, and seal facies.

Herein, we focus on one of these stratigraphic misconceptions, which deals with the development and sedimentary infill of the Late Jurassic Gotnia Basin, and its relationship with the aggrading platform of the Rimthan Arch. Our literature based re-interpretation proposes a mostly eustatically driven control, whereby the shallow water platform of the Rimthan Arch followed sea level rise, and the Gotnia Basin became a starved intra shelf basin. This revised stratigraphic interpretation has important consequences for the lateral facies relationships, and overall tectono-sedimentary understanding of the area, as well as for the petroleum habitat.
Investigation on the Kinetic Behavior of Gas Hydrates Based on Induction Time for a High CO2 Mixed Gas Multiphase Pipeline System
Authors: Sayani Jai Krishna , Yadavalli Sravya Sri , Mamidi Lokesh Teja , Kamireddi Venkateswara Rao
Published: November 2020

In this work, an experimental investigation has been carried out to understand the Kinetic behavior of gas hydrates formation in a multiphase gas dominant pipeline system. The multiphase system consists of Crude oil, Natural Gas system with high Carbon dioxide and deionized water. Experiments are conducted using the Raman Gas hydrate reactor with the operating conditions in line with the real time conditions. The Induction time was calculated for all the experiments and the kinetic behavior was evaluated. Also, a statistical regression model has been developed to predict the induction time. Also, this model is used for evaluating the most influential parameters on induction time prediction. It was found that the Induction time plays a major role in the kinetics of gas hydrates. The observations suggested that the higher the induction, the gas hydrates formation initiation is delayed.

Keywords: Multiphase Pipelines, Gas Hydrates, Kinetic Behavior, Statistical Regression Analysis.
Enhancing Directional Performance of PDC Drill Bits by Removing Extraneous Geometry
Authors: Bailey Michael James , Thomas Adam Xavier , Doudou Sofiane , El Kotob Mohamad , Al-Shukaili Ahmed Hamed , Al-Rawahi Imad Salem
Published: November 2020

This paper details the inception, modeling, laboratory, and field testing of a concept polycrystalline diamond compact (PDC) drill bit when removing its vestigial features. The extent to which length, gauge geometry, and bit design can affect directional response on push-the-bit rotary steerable systems (RSS) and a bent housing motor is examined. Results from laboratory testing provided feedback into analytical models for validation and are then field-tested in several different directional applications.

A comprehensive study was conducted to determine the benefits of removing the bit shank, which can be considered a redundant structure, alike the human appendix. Following this, both a steering-sensitive drill string model and computer-aided design (CAD) analyses were conducted to predict directional response and steering force values of both conventional and short-shank configurations. Drill bits were then manufactured and repeatedly tested on a push-the-bit RSS tool in a horizontal drill test. The testing results were used to validate and optimize the drill string model. This validated model was then used to design a drill bit for a field application where directional work was historically challenging.

The results from this paper focus on validating the short-shank concept known as the ultra-short make-up (USMU) bit via the drill string model and rigorous testing, as well as confirming the potential drilling benefits in challenging directional applications. The initial assumptions and approach from the drill string model and CAD analyses are presented. Validation by several high and low side tests on push the-bit RSS using drill bits with and without the short-shank modification were conducted. The dependent variables for testing were the directional capability, bit stability, borehole quality, and gauge pad-to-borehole interaction while biasing. The drilling parameters were kept constant to allow for a fair comparison of this concept design. The results of the post-horizontal testing were examined against the drill string model and adaptations made to both the model and its initial assumptions. This concept was then field-tested in a challenging directional application in Oman where steerable roller cone bits were predominately used. This led to back-to-back field rate-of-penetration (ROP) records, stable tool face, and excellent steering response from two hole sizes.

The vestigial concept generally applies to genetically determined structures or attributes that have apparently lost most or all their ancestral functions, such as a human's appendix or coccyx. This approach has rarely been used to drive technological developments within oil and gas tools. It also gives a refreshing new framework for concept, testing, and validation of changes to this unique directional drill bit design. A future development phase of this concept is to test it on the various rotary steerable systems and beyond.
Surfactant–Polymer Flooding at High Temperature and High Salinity: Promising Lab Scale Experiments in Challenging Conditions
Authors: Klimenko Alexandra , Molinier Valérie , Dubos Fabienne , Joly Michèle , Saint-Loubert Marcelle , Jouenne Stéphane , Passade-Boupat Nicolas , Bourrel Maurice
Published: November 2020

Performing Surfactant-Polymer (SP) flooding in High Salinity and High Temperature (HS-HT) conditions - up to 297 g/L TDS formation brine and 105°C-120°C - is challenging, both as regards the products selection and the implementation of the experimental workflow, from the selection tests of the surfactants and polymers to the corefloods, which need to be performed in an oxygen-free environment to reproduce field test conditions. In this work, we show our recent lab developments of SP formulations for different HS-HT conditions for limestone and sandstone reservoirs, both in terms of efficiency of chemicals in such conditions, and technical aspects.

Specific polymers and surfactants have been selected based on chemical stability and efficiency. The main surfactants have been chosen in the ethoxylated carboxylates and ethoxylated sulfonates series, and they have been formulated in order to reach optimal salinities in the 80-130 g/L TDS range. Special attention has been paid to the impact of the divalent cations on the physicochemical behavior.

These surfactant formulations were tested in corefloods using SAV10 as thermally stable polymer and taking into account the change in physicochemical phase behavior with oil saturation. Corefloods were carried out in oxygen-free conditions as well as pipettes study and surfactant thermal stability tests, since polymer and surfactants degrade in presence of oxygen at such high temperature.

Our results show a good efficiency of the formulations based on ethoxylated sulfonates on limestones (Residual oil saturation (Sorc) ~9%) with a retention of 0.26 mg/g of rock, whereas formulations based on ethoxylated carboxylates performed well on quartz sandpack (Sorc ~ 1-5%). The latter however gave lower recovery and high retention on limestones.

This work describes the development workflow and testing procedures to operate chemical EOR in very harsh conditions. As a result, we demonstrate that efficient HS-HT SP formulations are now available.
Processing Ultra–High Density 3D Seismic Surveys: An Abu Dhabi Case Study
Authors: Alkatheeri Tayammum , Cambois Guillaume , Mahgoub Mohamed , Nyein Glenn , Vasilyev Pavel , Mihaljevic Ivica , Doheim Mohamed
Published: November 2020

A new land ‘nimble node’ acquisition system was developed to deliver economical high-quality seismic data with the lightest and lowest-cost seismic channel system in the seismic industry. Besides the advantages in terms of environmental impact and operational safety, the design goal of the system is improvement of data quality by reducing the cost barriers to acquiring high-density seismic surveys. The present case study examines deployment of the nimble node system in Abu Dhabi, United Arab Emirates. ADNOC conducted a pilot survey in 2019 that involved approximately 50,000 single-sensor nodes laid-out on a 12.5 m × 12.5 m grid combined with source point interval of 12.5 m × 100 m source line interval. The acquisition of 81 sq km was completed ahead of planned schedule and field data quality met expectation. To accelerate acquisition turnaround, sources were vibrated simultaneously where only a minimal ‘no offset/time limiting’ rule was applied. While this approach had the advantage of greatly reducing cost and turnaround time for the field operations, it requires an efficient separation algorithm that identifies and removes the simultaneous-source interference while leaving the prime shot energy intact. We provide a summary of the processing efforts required to exploit the high-density data set in full, focusing on noise attenuation, surface consistent processes, and the improvements achieved in the final imaging over that of the legacy survey.
Looking at the Bigger Picture - Better Understanding of Well Behavior through Integration of Petrophysical, Production Logging and Corrosion Evaluation Data in a Challenging Environment, Ensuring Maximum Well Life and Overall Productivity
Authors: Chitre Sunil , Mustafa Hammad , Anurag Atul Kumar , Bazuhair Ahmed Khalid , Kuliyev Myrat , Javid Khalid , Anjum Usman , Sookram Neil , AlHaji Latifa , Al-Kindi Zaid , Afeefi Baraka Said , Jabour George
Published: November 2020

This paper describes optimal field development and appraisal in complex reservoirs and challenging environments in field ‘ABC’. Most of the wells are laterals with ICD (lower) completions across heterogeneous carbonate reservoirs. Highly corrosive environments i.e. up to 20% H2S present an added risk, particularly in the event of water encroachment. Optimal development needs a multi-disciplinary surveillance approach involving an integration of input form stakeholders, including geoscience and petroleum engineering, to ensure productivity optimization during the whole life of the field.

Field ABC is an offshore field with extremely heterogeneous carbonate reservoirs and acid stimulation is usually done to improve production. The wells in the field are mostly horizontal, oil producers with ICD lower completions. The upper completion uses carbon steel L80 and for corrosion mitigation, inhibitors are injected through chemical injection valves. In this paper, a pilot well is reviewed where a methodical approach was used for evaluation. Baseline production logging and reservoir saturation monitoring were done in the lower completion and a corrosion log was acquired in both the upper and lower completions. Data acquired was integrated and observations show that the measurements correlate well with each other.

This case study integrates and correlates downhole zonal contribution, phase holdups, pressure and temperature data from production logging with metal loss data from a high-resolution multi-finger caliper tool. Well trajectory shows a depression across the heel of the well which is incidentally between the EOT and the topmost ICD. Although there is no water production at surface, a static water sump is observed across this depression on the production logs. This static water is possibly completion fluid or unremoved fluid from the acid job. Minor localized corrosion is also observed across the same depression on the corrosion logs, also confirming presence of some water. The H2S production and the presence of water is an added risk to completion integrity as it creates a corrosive environment. Therefore, in such cases it will be necessary to monitor the production and corrosion at regular intervals of time.

This case study shows that by applying a multi-disciplinary approach and integrating various measurements, well conditions can be viewed not just as pieces of a puzzle but as a complete picture to improve the understanding of the well behavior. Time-lapse monitoring of production and corrosion along with reservoir saturation is also necessary to prevent surprises and help in making informed decisions towards better field development.