bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Integrated Ensemble-Based Uncertainty Centric Approach to Address Multi-Disciplinary Reservoir Challenges While Accelerating Subsurface Modeling Process in an Onshore Field, Abu Dhabi, UAE
Authors: Alqallabi Salahaldeen , Khan Abdul Saboor , Phade Anish , Gacem Mohamed Tarik , Adli Mustapha , Al-Jenaibi Faisal , Mansur Sheharyar , Malla Lyes , Benedictis Dario 
Published: September 2021

Abstract
The aim of this study is to demonstrate the value of a fully integrated ensemble-based modeling approach for an onshore field in Abu Dhabi. Model uncertainties are included in both static and dynamic domains and valuable insights are achieved in record time of nine-weeks with very promising results.
Workflows are established to honor the recommended static and dynamic modeling processes suited to the complexity of the field. Realistic sedimentological, structural and dynamic reservoir parameter uncertainties are identified and propagated to obtain realistic variability in the reservoir simulator response. These integrated workflows are used to generate an ensemble of equi-probable reservoir models. All realizations in the ensemble are then history-matched simultaneously before carrying out the production predictions using the entire ensemble.
Analysis of the updates made during the history-matching process demonstrates valuable insights to the reservoir such as the presence of enhanced permeability streaks. These represent a challenge in the explicit modeling process due to the complex responses on the well log profiles. However, results analysis of the history matched ensemble shows that the location of high permeability updates generated by the history matching process is consistent with geological observations of enhanced permeability streaks in cores and the sequence stratigraphic framework. Additionally, post processing of available PLT data as a blind test show trends of fluid flow along horizontal wells are well captured, increasing confidence in the geologic consistency of the ensemble of models. This modeling approach provides an ensemble of history- matched reservoir models having an excellent match for both field and individual wells’ observed field production data. Furthermore, with the recommended modeling workflows, the generated models are geologically consistent and honor inherent correlations in the input data. Forecast of this ensemble of models enables realistic uncertainties in dynamic responses to be quantified, providing insights for informed reservoir management decisions and risk mitigation.
Analysis of forecasted ensemble dynamic responses help evaluating performance of existing infill targets and delineate new infill targets while understanding the associated risks under both static and dynamic uncertainty. Repeatable workflows allow incorporation of new data in a robust manner and accelerates time from model building to decision making.
Simplified Solution for Managed Pressure Drilling - System that Drillers Can Operate
Authors: Patil Harshad , Knight Ian , Hovland Svein , Dietrich Earl , Boutalbi Said , Leal Jerib , Gonzalez Rick , Matherne Greg 
Published: September 2021

Abstract
Until recently many of the wells on US land that were drilled using Managed Pressure Drilling (MPD) technology utilized one size fits all equipment designed for the offshore market. Since the cost and personnel requirements needed to run the offshore manifolds became a challenge due to market conditions and Covid-19 restrictions, the drillers sought a cost effective and simpler system to conduct their day-to- day operations. The challenge was to drill long laterals in Permian and Haynesville without losing the necessary MPD functionality that proved beneficial to reduce the risks associated with safety and to enhance drilling efficiency. For the MPD control system experts, the task was to correctly identify and automate MPD system’s functionality that would be of greatest use to the drillers to sustain their drilling performance.
The concept of developing an easier to operate control system was undertaken wherein system accuracy and precision was maintained at the forefront of the development process. Electric motors/actuators and necessary drivers that could work directly on rig power were selected and tested. Control system logic that operates the chokes was modified to quickly adapt to the changes in drilling conditions, maintaining the necessary accuracy. This was done by studying and understanding drillers activities and behaviors like automated pump ramp down speed during connections, pipe movement during tripping etc. Specific MPD engineering charts, simple to decipher graphs, and necessary calculation tables were developed for the drillers to use for managing bottomhole pressures. Calculations which included specific schedules for spotting weighted pills were provided to maintain simplicity of the operations and something the drillers could easily execute.
Today, many drillers are using this MPD solution to drill long laterals (Hovland et.al 2020). This trend is slowly leading to reduction of rig MPD personnel, especially during Covid-19, while the drillers are getting familiar with and operating MPD systems. A few of the crucial items that have allowed the drillers to run MPD on their own include MPD controls connected to drilling automation systems and the subsequent continuous revision of these controls based on understanding drillers tasks and needs. The use of electric motors enabled quick adoption to the changing drilling conditions while making connections, tripping etc.
The furnished MPD calculations and graphs that drillers could follow for applying required MPD choke pressures kept MPD adaption simpler. The modifications made to the MPD choke controls geared towards facilitating necessary automation enabled the drillers to get trained in few days and operate the MPD systems while maintaining the same level of speed and performance.
Catastrophic Events and Human Error: A Few Rotten Apples or Organizational Dysfunction?
Authors: Bridle Peter 
Published: September 2021

Abstract
By July of 2021, it would have been 33 years since the 1988 Piper Alpha tragedy in the UK sector of the North Sea where 167 oil field workers lost their lives. Without question, the incident was a watershed event for the international oil and gas industry. And not simply because of the immediate toll in human lives lost, but also in terms of the devasting aftermath endured by countless friends, families and loved ones whose lives were forever changed on that fateful day. The tragedy also served to illustrate how much work would be needed by the oil and gas industry to fully understand and better manage those operating risks that possessed the potential for catastrophic loss in terms of business cost and reputational impact.
In the wake of the public enquiry that followed and chaired by Lord Cullen of Whitekirk, one of the principal recommendations resulting from the disaster required that the international oil and gas industry do a much better job in determining both its major hazards (i.e. major operating risks) and in creating the necessary operating conditions to demonstrate that such things were being well managed. The objective being to provide tangible assurance that the likelihood of the industry ever incurring such a calamitous event again in the future had been reduced to as low as reasonably practicable (ALARP).
In taking its responsibilities very seriously, the international oil and gas industry responded by raising the profile of the management of Health, Safety, and the Environment (HSE) across the wide spectrum of its global operations. By the mid-nineties, the industry had implemented comprehensive and structured systems of work within the framework of purposely built HSE Management Systems using templates designed and developed for the industry via the International Oil and Gas Producers (IOGP)*.
Delivering Automated Reservoir Management with Birth of the First Ever Universal Inflow Control System UICS
Authors: Killie Rune , Paterson Grant J. , Lager Thorleif 
Published: September 2021

Abstract
Conventional ICDs were invented for long horizontal wells to promote a more uniform inflow profile. Later, AICDs were developed, which utilize viscosity contrast between fluids to impose a larger hydraulic resistance in sections with inflow of undesired fluids, like gas and water. However, these AICD technologies cannot be used to choke back inflow of water in reservoirs where oil and water have similar viscosities, and they also tend to impose large pressure drops even for single-phase oil at high flow rates. The objective of the work presented here has therefore been to develop an inflow control technology that removes these limitations.
The resulting Density Activated Recovery (DAR™) technology utilizes difference in fluid density rather than viscosity contrast to control fluids downhole. It is a fully autonomous, binary system that is either fully open or closed, where "closed" means that it only allows a small pilot flow. More specifically, it can be considered a "dual ICD" with flow through a large port when open, and a small port when "closed". The flow capacity and choking efficiency are therefore fully defined by the diameters of these two ports. Furthermore, it can close and reopen at any pre-determined water and gas fractions, that are completely insensitive to flow rate, viscosity and Reynolds number. This makes it universally applicable to control any wellbore fluid along the entire reservoir section.
After successful prototype testing in 2018, the DAR technology has now undergone a comprehensive full-scale system-qualification program including a final flow performance test where the system was tested at 240 bar and 90ºC with saturated 0.8 cP oil. The tests demonstrated up to seven times higher flow capacity with the density-based DAR technology compared with viscosity-dependent AICD technologies. The system successfully and repeatedly closed and reopened for both gas and water. As oil and water had similar viscosities, the tests also proved how this technology can be used to stop undesired inflow of water in light-oil reservoirs.
Being insensitive to flow rate, the DAR system is also insensitive to local variations in pressure and productivity along the reservoir section, which reduces the negative consequences of geological uncertainty and allows the same design to be used at every location in the well. It can also be configured to ensure complete mud removal during well cleanup and can even stop inflow of water in gas wells, where the undesired fluid has higher viscosity than the desired fluid. More importantly, this technology can deliver automated reservoir management to a level where it influences how wells are drilled and fields are developed. Accelerated oil production and the reduced need for reinjection of gas/water will also reduce the associated greenhouse gas (GHG) emissions considerably.
Well Connectivity Analysis with Deep Learning
Authors: Li Yuanjun , Suzuki Satomi , Horne Roland 
Published: September 2021

Abstract
Knowledge of well connectivity in a reservoir is crucial, especially for early-stage field development and water injection management. However, traditional interference tests can often take several weeks or even longer depending on the distance between wells and the hydraulic diffusivity of the reservoir. Therefore, instead of physically shutting in production wells, we can take advantage of deep learning methods to perform virtual interference tests.
In this study, we first used the historical field data to train the deep learning model, a modified Long- and Short-term Time-series network (LSTNet). This model combines the Convolution Neural Network (CNN) to extract short-term local dependency patterns, the Recurrent Neural Network (RNN) to discover long-term patterns for time series trends, and a traditional autoregressive model to alleviate the scale insensitive problem. To address the time-lag issue in signal propagation, we employed a skip-recurrent structure that extends the existing RNN structure by connecting a current state with a previous state when the flow rate signal from an adjacent well starts to impact the observation well. In addition, we found that wells connected to the same manifold usually have similar liquid production patterns, which can lead to false causation of subsurface pressure communication. Thus we enhanced the model performance by using external feature differences to remove the surface connection in the data, thereby reducing input similarity. This enhancement can also amplify the weak signal and thus distinguish input signals. To examine the deep learning model, we used the datasets generated from Norne Field with two different geological settings: sealing and nonsealing cases. The production wells are placed at two sides of the fault to test the false-negative prediction.
With these improvements and with parameter tuning, the modified LSTNet model could successfully indicate the well connectivity for the nonsealing cases and reveal the sealing structures in the sealing cases based on the historical data. The deep learning method we employed in this work can predict well pressure without using hand-crafted features, which are usually formed based on flow patterns and geological settings. Thus, this method should be applicable to general cases and more intuitive. Furthermore, this virtual interference test with a deep learning framework can avoid production loss.
The Digital Transformation of the Knowledge Worker
Authors: Creus Fernando Luis 
Published: September 2021

Abstract
Technological advances unveil a dual reality in the oil and gas Industry. On one hand, the benefits of blockchain and artificial intelligence (AI), among others, has arrived to revolutionize the industry. On the other hand, industry professionals remain trapped in bureaucratic processes that undermine their performance. The diagnosis: knowledge workers, responsible for optimizing the recovery and economic performance of the fields, are the missing link in the digital transformation chain. They are suffering the digitalization of the status quo.
This paper puts forward a broad digital transformation framework designed to increase the knowledge worker's productivity. Digital transformation is not just about the implementation and use of cutting-edge technologies. It is also the response to digital trends, and about adopting new processes and redesigning existing ones to compete effectively in an increasingly digital world. Prioritizing technology as the ultimate goal puts the business processes and the knowledge workers aside from the discussion.
The key to this proposal is rethinking the business model according to the possibilities of new technologies based on a six-dimension scheme:Corporate strategy: It defines the long-term vision and investment criteria for value creation. Technology is an element within a business scheme that should not be analyzed in isolation.Digital strategy: Within the corporate strategy, what operational and strategic role does technology play? Should it only support the company's operation, or should it drive strategic reinvention?Culture: While digital transformation is the company's response to digital trends, culture is the muscle that provides (or not) the attributes required to succeed in this transformation endeavor. Innovation and creativity should be promoted as part of the company's DNA.Knowledge processes: A business model, built on new technologies, will necessarily impose new and automated practices. While the automation of physical processes is a fact, the automation of knowledge processes is the weakest link.Data governance: It defines the necessary conditions that guarantee the quality of the information and its strategic acquisition. Two elements are a must: the automation of processes, thereby avoiding arbitrariness in data management; and centralized databases, thereby eliminating data duplicity and criteria discrepancy.Data Science: At this point in the model, the company has efficient, automatic, and fast processes, assuring the quality and availability of the data from its conception to the final storage. Then, data scientists will have all the means, and a clear and aligned vision (corporate strategy) to extract meaningful insights for the business.
Issue with Stone-II Three Phase Permeability Model, and A Novel Robust Fundamentals-Based Alternative to It
Authors: Gupta Subodh 
Published: September 2021

Abstract
The objective of this paper is to present a fundamentals-based, consistent with observation, three-phase flow model that avoids the pitfalls of conventional models such as Stone-II or Baker's three-phase permeability models.
While investigating the myth of residual oil saturation in SAGD with comparing model generated results against field data, Gupta et al. (2020) highlighted the difficulty in matching observed residual oil saturation in steamed reservoir with Stone-II and Baker's linear models. Though the use of Stone-II model is very popular for three-phase flow across the industry, one issue in the context of gravity drainage is how it appears to counter-intuitively limit the flow of oil when water is present near its irreducible saturation.
The current work begins with describing the problem with existing combinatorial methods such as Stone-II, which in turn combine the water-oil, and gas-oil relative permeability curves to yield the oil relative permeability curve in presence of water and gas. Then starting with the fundamentals of laminar flow in capillaries and with successive analogical formulations, it develops expressions that directly yield the relative permeabilities for all three phases. In this it assumes a pore size distribution approximated by functions used earlier in the literature for deriving two-phase relative permeability curves. The outlined approach by-passes the need for having combinatorial functions such as prescribed by Stone or Baker.
The model so developed is simple to use, and it avoids the unnatural phenomenon or discrepancy due to a mathematical artefact described in the context of Stone-II above. The model also explains why in the past some researchers have found relative permeability to be a function of temperature. The new model is also amenable to be determined experimentally, instead of being based on an assumed pore-size distribution. In that context it serves as a set of skeletal functions of known dependencies on various saturations, leaving constants to be determined experimentally.
The novelty of the work is in development of a three-phase relative permeability model that is based on fundamentals of flow in fine channels and which explains the observed results in the context of flow in porous media better. The significance of the work includes, aside from predicting results more in line with expectations and an explanation of temperature dependent relative permeabilities of oil, a more reliable time dependent residual oleic-phase saturation in the context of gravity-based oil recovery methods.
The Case for Combining Well Intervention Solutions to Optimize Production and Reduce Risk Exposure
Authors: Meling Eyvind Morten , Mourani Houssam , Schwanitz Brian Joseph 
Published: September 2021

Abstract
While optimizing hydrocarbon production, combining well intervention solutions can enable significant benefits due to reductions in risk exposure: fewer rig-ups and downs, less in-the-hole operating time and the carbon production and costs associated with rig time, especially when working from sub-sea intervention vessels. Operators in general, prefer to achieve multiple intervention objectives in a single descent in the well, if the operations complexity does not increase the risk exposure to an unacceptable level. Often, the risk of a mis-run, causing a second run, meets the cost vs value criteria for acceptable risk, when the large operating time savings of a successful combined run is considered.
In collaboration with a mechanical e-line provider, North Sea operators developed three reliable combination solutions which increased their operational efficiency. Combining these most run services under more standard, common scope of work procedures, saved the operator time in planning, execution, risk exposure and money, while enabling them to produce hydrocarbons in the saved time. This paper will present the technology involved with these combined services, use a typical example of each and the cost savings achieved.
Downhole Monitoring of Fractures in a Waterflood Development – Part II
Authors: Kohli Abhinandan , Kelder Oscar , Castelijns Ralph , Eijs Rob van , Volkov Maxim 
Published: September 2021

Abstract
For maintenance of the reservoir pressures and enhanced oil recovery in oil producing formations, waterflooding is often implemented by the Operators. This is achieved by drilling injection wells or converting the oil producing wells into injectors. The injection wells are located at carefully selected points in the oilfield so that the water displaces as much oil as possible to the production wells before the water starts to break through. A significant saving in an oilfield development can be obtained by reducing the actual number of injecting wells and increasing each of the injector wells’ capacity for injection. Balancing the injection and produced volumes often involves injecting at high pressures leading to the fracture of the reservoir rocks along a plane intersecting the wellbore. This happens when injection pressure exceeds the minimal principal stress and the tensile strength of the rock, thereby creating a hydraulic fracture. With continuous injection, these fractures start propagating into the reservoir and may reach the reservoir caprock, which may decrease the integrity and possibly lead to out of zone injection.
The study of evaluation of downhole fracture monitoring is divided into two parts. In the first part of the paper (Kohli, et al., 2021), a downhole verification approach to identify the fracture initiation point(s) is the focus. It describes the planning, execution and interpretation of the downhole data. This includes spectral acoustic monitoring and modelling of the temperature responses to quantify the injectivity profile.
In this second part of the paper, the direct business impact is discussed by further integration of acoustic monitoring and temperature modeling data with detailed results from of fracture dimension (height) measurement by means of pressure fall off tests. Combined, both studies form an integrated approach that the operator took to prove that the fracture network propagation remains within the reservoir and that the top seal integrity is maintained.
Through Barrier Diagnostics to Locate Multiple Barrier Failures in Complex Well Failure Scenario and to Enable Successful P&A
Authors: Volkov Maxim , Zaripova Asiya , Sikander Sultan , Ezwai Jamal , Altaeb Islam , Elbouma Osama 
Published: September 2021

Abstract

Objectives/Scope
A 60-year-old well exhibited a leak at the surface and sustained annuli pressure (SAP) in all three annuli - A, B and C. The age of the well coupled with the symptoms suggested a complex multi-barrier failure scenario that needed to be diagnosed quickly and accurately so that the well could be secured safely. The paper shows how the comprehensive set of downhole diagnostics, including metal and cement barriers integrity assessment, aided in planning and execution of well intervention to secure the indicated failures.
The well intervention team selected an approach to investigate the barriers status prior the rig came to the location. Surface diagnostics included evaluation of pressure trends, completion design, leak fluid composition and drilling records analysis which guided the selection of downhole survey. The input parameters for downhole through barrier diagnostics were:
Downhole through barrier diagnostics targeted the evaluation of leak paths and failures in well barriers and included:
This paper explores the concept, planning, execution and achieved results of the downhole diagnostics performed and how the results were implemented by Operator.