bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fault Planes Materials Fill Characteristics, UAE
Authors: Noufal Abdelwahab 
Published: December 2021

Abstract
Abu Dhabi subsurface fault populations triggered basin system in diverse directions, because of their significant role as fluid pathways. Studying fault infill materials, fault geometries, zone architecture and sealing properties from outcrops as analogues to the subsurface of Abu Dhabi, and combining these with well data and cores are the main objectives of this paper. The fault core around the fault plane and in areas of overlap between fault segments and around the fault tip include slip surfaces and deformed rocks such as fault gouge, breccia, and lenses of host rock, shale smear, salt flux and diagenetic features.
Structural geometry of the fault zone architecture and fault plane infill is mainly based on the competency contrast of the materials, that are behaving in ductile or in a brittle manner, which are distributed in the subsurface of Abu Dhabi sedimentary sequences with variable thicknesses. Brittleness is producing lenses, breccia and gouge, while, ductile intervals (principally shales and salt), evolved in smear and flux. The fault and fractures are behaving in a sealy or leaky ways is mainly dependent on the percentage of these materials in the fault deformation zone. The reservoir sections distancing from shale and salt layers are affected by diagenetic impact of the carbonates filling fault zones by recrystallized calcite and dolomite.
Musandam area, Ras Al Khaima (RAK), and Jabal Hafit (JH) on the northeast- and eastern-side of the UAE represents good surface analogues for studying fault materials infill characteristics. To approach this, several samples, picked from fault planes, were analysed. NW-trending faults system show more dominant calcite, dolomite, anhydrites and those closer to salt and shale intervals are showing smearing of the ductile infill. The other linked segments and transfer faults of other directions are represented by a lesser percentage of infill. In areas of gravitational tectonics, the decollement ductile interval is intruded in differently oriented open fractures.
The studied outcrops of the offshore salt islands and onshore Jabal Al Dhanna (JD) showing salt flux in the surrounding layers that intruded by the salt. The fractures and faults of the surrounding layers and the embedment insoluble layers are highly deformed and showing nearly total seal. As the salt behaving in an isotropic manner, the deformation can be measured clearly by its impact on the surrounding and embedment's insoluble rocks.
The faults/fractures behaviour is vicious in migrating hydrocarbons, production enhancement and hydraulic fracturing propagation.
Document Layout Analysis Using Detection Transformers
Authors: Pillai Prashanth , Mangsuli Purnaprajna 
Published: December 2021

Abstract
In the O&G (Oil & Gas) industry, unstructured data sources such as technical reports on hydrocarbon production, daily drilling, well construction, etc. contain valuable information. This information however is conveyed through various formats such as tables, forms, text, figures, etc. Detecting these different entities in documents is essential for building a structured representation of the information within and for automated processing of documents at scale. Our work presents a document layout analysis workflow to detect/localize different entities based on a deep learning-based framework.
The workflow comprises of a deep learning-based object-detection framework based on transformers to identify the spatial location of entities in a document page. The key elements of the object-detection pipeline include a residual network backbone for feature extraction and an encoder-decoder transformer based on the latest detection transformers (DETR) to predict object-bounding boxes and category labels. The object detection is formulated as a direct set prediction task using bipartite matching while also eliminating conventional operations like anchor box generation and non-maximal suppression. The availability of sufficient publicly available document layout data sets that incorporate the artifacts observed in historical O&G technical reports is often a major challenge. We attempt to address this challenge by using a novel training data augmentation methodology. The dense occurrence of elements in a page can often introduce uncertainties resulting in bounding boxes cutting through text content. We adopt a bounding box post-processing methodology to refine the bounding box coordinates to minimize undercuts.
The proposed document layout analysis pipeline was trained to detect entity types such as headings, text blocks, tables, forms, and images/charts in a document page. A wide range of pages from lithology, stratigraphy, drilling, and field development reports were used for model training. The reports also included a considerable number of historical scanned reports. The trained object-detection model was evaluated on a test data set prepared from the O&G reports. DETR demonstrated superior performance when compared with the Mask R-CNN on our dataset.
Field Realization of Adaptive Reservoir Simulation for Steam Injection Forecasting
Authors: Ursegov Stanislav , Taraskin Evgenii , Zakharian Armen 
Published: December 2021

Abstract
Globally, steam injection for heavy and high-viscous oil recovery is increasing, including carbonate reservoirs. Lack of full understanding such reservoir heating and limited information about production and injection rates of individual wells require to forecast steam injection not only deterministic and simple liquid displacement characteristic modeling types, but also the data-driven one, which covers the adaptive modeling. The implementation and validation of the adaptive system is presented in this paper by one of the world's largest carbonate reservoirs with heavy and high-viscous oil of the Usinsk field.
Steam injection forecasting in such reservoirs is complicated by the unstable well interactions and relatively low additional oil production. In the adaptive geological model, vertical dimensions of cells are similar to gross thicknesses of stratigraphic layers. Geological parameters of cells with drilled wells do not necessarily match actual parameters of those wells since the cells include information of neighboring wells. During the adaptive hydrodynamic modeling, a reservoir pressure is reproduced by cumulative production and injection allocation among the 3D grid cells. Steam injection forecasting is firstly based on the liquid displacement characteristics, which are later modified considering well interactions.
To estimate actual oil production of steamflooding using the reservoir adaptive geological and hydrodynamic models, dimensionless interaction coefficients of injection and production wells were first calculated. Then, fuzzy logic functions were created to evaluate the base oil production of reacting wells. For most of those wells, actual oil production was 25 – 30 % higher than the base case. Oil production of steamflooding for the next three-year period was carried out by modeling two options of the reservoir further development - with and without steam injection. Generally, forecasted oil production of the option with steam injection was about 5 % higher. The forecasting effectiveness of cyclic steam stimulations of production wells was done using the cross-section method, when the test sample was divided into two groups - the best and the worst, for which the average forecasted oil rates after the stimulations were respectively higher or lower than the average actual oil rate after the stimulations for the entire sample. The difference between the average actual oil rates after the stimulations of the best and the worst groups was 32 %, i.e. this is in how much the actual oil production could have increased if only the best group of the sample had been treated.
An Experimental Investigation of High and Low Salinity Waterflood Displacement Under the Steady-State Condition
Authors: Aljaberi Abdulla , Farzaneh Seyed Amir , Aghabozorgi Shokoufeh , Ataei Mohammad Saeid , Sohrabi Mehran 
Published: December 2021

Abstract
Oil recovery by low salinity waterflood is significantly affected by fluid-fluid interaction through the micro-dispersion effect. This interaction influences rock wettability and relative permeability functions. Therefore, to gain a better insight into multiphase flow in porous media and perform numerical simulations, reliable relative permeability data is crucial. Unsteady-state or steady-state displacement methods are commonly used in the laboratory to measure water-oil relative permeability curves of a core sample. Experimentally, the unsteady-state core flood technique is more straightforward and less time-consuming compared to the steady-state method. However, the obtained data is limited to a small saturation range, and the associated uncertainty is not negligible. On the other hand, the steady-state method provides a more accurate dataset of two-phase relative permeability needed in the reservoir simulator for a reliable prediction of the high salinity and low salinity waterflood displacement performance.
Considering the limitations of the unsteady state method, steady-state high salinity and low salinity brine experiments waterflood experiments were performed to compare the obtained relative permeability curves. The experiments were performed on a carbonate reservoir sample using a live reservoir crude oil under reservoir conditions. The test was designed so that the production and pressure drop curve covers a wider saturation range and provides enough data for analysis. Consequently, reliable relative permeability functions were obtained, initially, for a better comparison and prediction of the high salinity and the low salinity waterflood injections and then, to quantify the effect of low salinity waterflood under steady-state conditions.
The results confirm the difference in relative permeability curves between high salinity and low salinity injections due to the micro-dispersion effect, which caused a decrease in water relative permeability and an increase in the oil relative permeability. These results also proved that low salinity brine can change the rock wettability from oil-wet or mixed-wet to more water-wet conditions. Furthermore, the obtained relative permeability curves extend across a substantial saturation range, making it valuable information required for numerical simulations. To the best of our knowledge, the reported data in this work is a pioneer in quantifying the impact of low salinity waterflood at steady-state conditions using a reservoir crude oil and reservoir rock, which is of utmost importance for the oil and gas industry.
Flourishing Production Optimization thru the Development of an Enhanced Testing Validity Methodology
Authors: Al Yateem Rakan , Al-Kadem Mohammad , Alodhiani Suliman , Kishi Majed 
Published: December 2021

Abstract
Rate testing has evolved over the years. From a simple composite separator system, the scope of rate testing has morphed into a broad spectrum of sophisticated downhole and surface technologies. Knowing well behavior, performance, and associated rate are the key factors of operating an entire field with the most reliable operating strategy, assuring maximum well-life time. In regard to well modeling and optimization, valid rate test data are crucial to predict well performance efficiently.
An in-house rate testing mechanism was developed to ensure proper delivery, accuracy, and validity of rate tests. The mechanism comprises a rate testing procedure and decision-making tree. The rate testing procedure includes regular checks of rate testing data reports. Also, the immediate resolution of rate testing equipment or communication issues is implemented through the utilization of an MPFM Advanced Monitoring System with automated logics. A decision-making tree constitutes pre- and post-testing process phases. The pre-testing process phase involves an assessment for rate testing readiness in terms of testing equipment and communication. The post-testing process phase includes an assessment for testing operation and rate test validity where rate test data are checked and validated based on production operational status.
The enhanced testing mechanism is a user-friendly guideline for testing requirements to ensure the completion of tests captured from testing equipment. The proper implementation of this rate testing mechanism enabled a high quality and accuracy of rate test data, resulting in an increase in rate testing validity by 30%. Also, the rate testing mechanism inspired a culture of continuous effective communication for all involved parties during the testing operation. The decision-making tree transforms the validation process from subjective thinking to a systematic workflow while integrating data from nearby wells with similar behavior. A high ownership level is exhibited by taking the immediate resolution of issues results in achieving high rate testing validity percentage. Running the process through standardized operating procedures is critical in generating consistent and predictable results of well performance. Additionally, accurate optimization and prediction of well performance have been realized by feeding the well model's data before and after attaining valid rate test data, which attests to the quality of the proposed rate testing mechanism.
Considering the importance of having a strategic rate testing mechanism, it is highly advised to have more frequent measurements to raise the accuracy of the measurements presented. An ideal strategic rate testing mechanism has to be economical enough to be placed in many production wells, allow the tests to be performed in an organized manner, improve measurement accuracy, and, more importantly, achieve automated and supervised well tests processes.
Cement Conundrum: Valuable Lessons Learned for Sustaining Production
Authors: Zulkipli Siti Najmi Farhan binti 
Published: December 2021

Abstract
Addressing wellbore integrity through cement evaluation has been an evergreen topic which frequently catches major operators by surprise due to premature water or gas breakthrough causing low production attainability from the wells. Managing idle well strings arising from integrity issues is also a challenge throughout the production period. The remedial solutions to these issues do not come conveniently and require high cost during late life well intervention which often erodes the well economic limit. A critical element of wellbore barrier which is cement integrity evaluation is proposed to be uplifted and given a new perspective to define success criteria for producer wells to achieve certain reserves addition and production recovery. This paper will highlight integrated factors affecting cement bond quality, impact to well production, potential remedies for poor cement bond observed leveraging on the enhanced workflow and new technology and way forward to proactively prevent the unwanted circumstances in the first opportunity taken. A set of recommendations and prioritization criteria for future cement improvement will be also highlighted.
Several case specific wells logged with variable cement bond evaluation tools are re-assessed and deep-dived to trace the root causes for unsatisfactory cement bond quality observed which include reservoir characteristics, understanding anomalies during drilling and cementing operation, identifying cement recipe used, log processing parameters applied and observing best practices during cementing operation to improve the quality. New and emerging cement evaluation technology inclusive of radioactive-based logging to meet specific well objectives will be also briefly discussed in terms of differences and technical deliverables.
Looking at each spectrum, results show that there are several interdependent factors contributing to poor cement bond quality observed. Accurate understanding of formation behavior, designing fit-for-purpose cement recipe and adequate planning for cementing operation on well-by-well basis are among the top- notch approaches to be applied for an acceptable cement bond quality and placement. Statistics show that 27% to 64% of production attainability is achieved by wells with good cement quality within the first 3 months of production and this increases to 85% to 98% up until 7 months of production period, while only 12% production attainability achieved for those wells with adverse cement quality issue. In another well, water cut as high as 47% since the first day of production is observed which keeps increasing up to 40% thereafter.
In a nutshell, cement evaluation exercise shall not be treated as vacuum, instead it requires an integrated foundation and close collaboration to materialize the desired outcomes. Arresting the issue with the right approach in the first place will be the enabler for optimum well performance and productivity to exceed the recovery target.
Advanced Research and Development in Unconventional Use of Tracer Technology for EOR and IOR: What lies beyond?
Authors: Chatterjee Monalisa , Toh Sean , Alshmakhy Ahmed , Bigno Yann , Hewitt Paul 
Published: December 2021

Abstract
Over the last few decades, tracers have provided crucial insights on fluid flow behavior assessing reservoir connectivity. For years, they had been viewed as mostly passive molecules that go with the flow of the injected fluid and uncover pathways between injectors and producers. The proposed paper sheds light on some interesting newer frontiers of tracer applications with unconventional uses to gain further flow insight from an oil and gas reservoir.
Although primarily developed for interwell applications, newer and more sophisticated genres of tracers have found their way to assist with well fluid flow behavior. Inflow tracer applications, used for phase flow diagnostics, have been around for a few decades now. However, with several parameters like physical space restrictions, temperature, solid support selection, multi-phase flow, initial surge and target concentrations at play, it was soon realised that an extended lifetime was needed to provide techno-economic benefits during reservoir monitoring. Microencapsulation of tracer molecules is one of the newer developed techniques that has shown significant extension to tracer life in controlled release tracer applications as well as improved dispersibility within fracking fluid. Newer synthesis mechanisms like microencapsulation have been developed to linearize inflow tracer release profiles that has led to a substantial increase in tracer lifetime. As the research and development progressed, newer tracers such as frac bead tracers were developed allowing long term fluid flowback monitoring in fracture stimulated wells.
In parallel, it is still an active field of investigation as to how tracers can be integrated with common downhole completion and topside equipment of a well to accurately detect early water breakthrough.
The paper discusses the advances in these target areas where chemistry is constantly being upgraded to suit end user needs. Novel applications and ‘out-of-the-box’ uses have been developed in the last couple of years where inflow tracers have found a modified use within the gas lift system in a well and integrated with the top-side flow arm of the well, eradicating the need for individual sampling of wells and detection of water breakthrough at an early onset, thus aiding timely decision making and improved recovery from the well. Real time analysis of tracers have attracted attention for quite some time now. The paper also discusses the latest development in this area and the challenges associated with real field applications.
While advancements in versatility of the tracer molecules have been published prior in literature, to the best of the authors’ knowledge, no work has been published to date that discusses the latest advances in unconventional uses of the tracer molecules aiding EOR and IOR processes.
Rapid and Efficient Waterflood Optimization Using Augmented AI Approach in a Complex Offshore Field
Authors: Ghedan Shawket , Surendra Meher , Maqui Agustin , Elwan Mahmoud , Kansao Rami , Mousa Hesham , Jha Raman , Korish Mahmoud , Olalotiti-lawal Feyisayo , Shahin Eman , El Sayed Mohamed , Eid Tarek , Rouis Lamia , Huang Qing 
Published: December 2021

Abstract
Waterfloods are amongst the most widely implemented methods for oil field development. Despite their vast implementation, operational bottlenecks such as lack of surveillance and optimization tools to guide fast paced decisions render most of these sub-optimal. This paper presents a novel machine-learning, reduced-physics approach to optimize an exceptionally complex off-shore waterflood in the Gulf of Suez.
Leveraging a hybrid data-driven and physics approach, the water flooding scheme in Nezzezat reservoir was optimized to improve reservoir voidage replacement, increase oil production, and reduce water production by identifying potential in wells. As a by-product of the study, a better understanding of the complex fault system was also achieved. Including the geological understanding and its uncertainty is one of the key elements that must be preserved. All geological attributes, along with production rates are used to solve for pressure and inter-well communication. This is later supplemented by machine-learning algorithm to solve for the fractional flow of inter-well connections.
Combining the inter-well connectivity and fractional flow, an optimization was performed to reach the best possible conditions for oil gains and water-cut reduction. A global optimization is possible thanks to the low computational demand of this approach, as thousands to millions of realizations must be run to reach the best solution while satisfying all constraints. This is all done in a fraction of the time it takes to run a traditional reservoir simulation.
For the present case, the paper will present the underlying physics and data-driven algorithms, along with the blind tests performed to validate the results. In addition to the method's inner workings, the paper will focus more on the results to guide operational decisions. This is inclusive of all the complex constraints of an offshore field, as well as the best reservoir management practices, when reaching optimal production and injection rates for each well. An increase in production was achieved with some reduction in water-cut, while honoring well and platform level limitations. While these represent the gains for a particular month, optimization scenarios can be run weekly or monthly to capture the dynamic nature of the problem and any operational limitations that might arise. The ability to update the models and run optimization scenarios effortlessly allows pro-active operational decisions to maximize the value of the asset.
The approach followed in this paper solves for the critical physics of the problem and supplements the remaining with machine learning algorithms. This novel and extremely practical approach facilitate the decision making to operate the field optimally.