bluuebunny/crossref_metadata_2025 huggingface dataset:
Document Layout Analysis Using Detection Transformers
Authors: Pillai Prashanth , Mangsuli Purnaprajna
Published: December 2021

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

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

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

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

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

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

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.
Development of an Online Soft Analyzer for the Continuous Analysis of BTEX Emissions from the Furnace of Sulfur Recovery Units
Authors: Dara Satyadileep , Ibrahim Salisu , Jagannath Anoop , Raj Abhijeet , Khan Ibrahim , Al Jenaibi Eisa
Published: December 2021

The oxidation of Benzene, Toluene, Ethylbenzene, and Xylenes (BTEX) in the furnace of SRUs at high temperature is an effective solution to prevent Claus catalyst deactivation in the downstream catalytic converters. However, the existing SRUs do not have the means to monitor BTEX emissions from Claus furnace due to lack of commercial online analyzers in the market. This often leads to excessive temperatures up to 1150 °C in the furnace to ensure BTEX destruction. Such high temperatures increase fuel gas consumption and CO emission and reduce sulfur recovery efficiency. To obtain continuous BTEX indication at the furnace exit, an online BTEX soft sensor model is developed to predict BTEX concentration at furnace exit. Subsequently, this soft sensor will be implemented in one of the SRUs of ADNOC Gas Processing. The BTEX soft sensor has been developed by constructing a compact kinetic model for aromatics destruction in the furnace based on the understanding of BTEX oxidation mechanisms derived using a detailed and well validated kinetic model developed previously. The kinetic model, including its rate parameters were incorporated into Hysys/Sulsim software, where both the reaction furnace and catalytic converters were simulated. The BTEX soft sensor has been validated with plant data from different ADNOC Gas Processing SRU trains under a wide range of feed conditions (particularly, with varying relative concentrations of H2S, CO2, and hydrocarbons in acid gas feed) in order to ensure its robustness and versatile predictive accuracy. The model predicts BTEX emissions from the reaction furnace under a wide range of operating conditions in the furnace with deviation not exceeding +/- 5 ppm. It also predicts the reaction furnace temperature (with a deviation of +/- 5%) and species composition from the furnace exit within a reasonable error margin. Presently, the model is in the process of being deployed in one of the SRUs of ADNO Gas Processing as an online soft sensor, where it can read the feed conditions, predict the BTEX exit concentration and write this value to the DCS. Thus, plant operators can monitor BTEX exit concentration on continuous basis and use it as a reliable basis to lower fuel gas co-firing rate in the furnace to achieve optimum furnace temperature that provide efficient BTEX destruction and low CO emission. The online soft analyzer, when deployed in SRU, will continuously predict BTEX emission from SRU furnace with high accuracy, which cannot be done experimentally in the plant or reliably using most of the existing commercial software. This approach can be used to seek favorable means of optimizing BTEX destruction to enhance sulfur recovery, while decreasing fuel gas consumption and carbon footprint in sulfur recovery units to reduce operating cost.
Understanding the Flow Dynamics of CO2 Plumes in the Subsurface
Authors: Bebb Florence Letitia , Evans Kate Clare Serena , Mukherjee Jagannath , Saeed Bilal , Christopher Geovani
Published: December 2021

There are several significant differences between the behavior of injected CO2 and reservoired hydrocarbons in the subsurface. These fundamental differences greatly influence the modeling of CO2 plumes.

Carbon capture, utilization, and storage (CCUS) is growing in importance in the exploration and production (E&P) regulatory environment with the Oil and Gas Climate Initiative (OGCI) making CCUS a priority. Companies need to prospect for storage sites and evaluate both the short-term risks and long-term fate of stored carbon dioxide (CO2).

Understanding the physics governing fluid flow is important to both CO2 storage and hydrocarbon exploration and production. In the last decade, there has been much research into the movement and migration of CO2 in the subsurface. A better understanding of the flow dynamics of CO2 plumes in the subsurface has highlighted a number of significant differences in modeling CO2 storage sites compared with hydrocarbon reservoir simulations. These differences can greatly influence reliability when modeling CO2 storage sites.
Prediction and Optimization of WAG Flooding by Using LSTM Neural Network Model in Middle East Carbonate Reservoir
Authors: Huang Ruijie , Wei Chenji , Li Baozhu , Yang Jian , Wu Suwei , Xu Xin , Ou Yajie , Xiong Lihui , Lou Yuankeli , Li Zhengzhong , Deng Ya , Zhang Chenjun
Published: December 2021

Production prediction continues to play an increasingly significant role in reservoir development adjustment and optimization, especially in water-alternating-gas (WAG) flooding. As artificial intelligence continues to develop, data-driven machine learning method can establish a robust model based on massive data to clarify development risks and challenges, predict development dynamic characteristics in advance. This study gathers over 15 years actual data from targeted carbonate reservoir and establishes a robust Long Short-Term Memory (LSTM) neural network prediction model based on correlation analysis, data cleaning, feature variables selection, hyper-parameters optimization and model evaluation to forecast oil production, gas-oil ratio (GOR), and water cut (WC) of WAG flooding. In comparison to traditional reservoir numerical simulation (RNS), LSTM neural networks have a huge advantage in terms of computational efficiency and prediction accuracy. The calculation time of LSTM method is 864% less than reservoir numerical simulation method, while prediction error of LSTM method is 261% less than RNS method. We classify producers into three types based on the prediction results and propose optimization measures aimed at the risks and challenges they faced. Field implementation indicates promising outcome with better reservoir support, lower GOR, lower WC, and stabler oil production. This study provides a novel direction for application of artificial intelligence in WAG flooding development and optimization.
Monitoring of Methane Emissions in Oil and Gas from Space: Matching Needs with Satellite System Capability, and Advantages of High Resolution Monitoring
Authors: Gauthier Jean-Francois
Published: December 2021

Satellites are a powerful tool in monitoring methane emissions around the world. In the last five years, many new systems have been both announced and deployed, each with different capabilities and designed for a specific purpose. With an increase in options also comes confusion as to how these systems can and should be used, especially in meeting the needs of the oil and gas industry. This paper will examine the different satellite systems available and explain what information they are best suited to provide.

The performance parameters of several current and future satellite systems will be presented and supported with recent examples when available. For example, the importance of factors like frequency of revisit, detection threshold, and spatial resolution will be discussed and contrasted with the needs of the oil and gas industry in gaining a more complete understanding of its methane emissions and enabling action to mitigate them.

Results from GHGSat's second generation of high-resolution satellites displaying measurements of methane plumes at oil and gas facilities around the world will be presented to demonstrate some of the advantages of the technology. These two satellites, GHGSat-C1 and C2 (Iris and Hugo), were launched in September 2020 and January 2021 respectively and have started delivering a tenfold improvement in performance after incorporating the lessons learned from their predecessor, GHGSat's demonstration satellite Claire.

Finally, the ability of these systems to work together and complement each other's capabilities to provide actionable insight to the oil and gas industry will be discussed.
Mitigation of Gas Condensate Banking Using an Integrated Chemical Approach
Authors: Hassan Amjed Mohammed , Mahmoud Mohamed Ahmed , Al-Nakhli Ayman Raja
Published: December 2021

In gas reservoirs, the well production can be reduced due to the development and accumulation of condensate in the near-wellbore zone. Various techniques are used to minimize the condensate damage and maintain hydrocarbon production. Hydraulic fracturing and wettability alteration techniques are the most effective methods. However, these techniques are expensive, especially in deep gas reservoirs. This paper introduces a new approach for mitigating condensate accumulation by integrating the hydraulic fracturing and wettability alteration treatments. The efficiency of two chemicals that can generate multiple fractures and alter the fracture surfaces to less condensate status is investigated in this work. Thermochemical fluids and chelating agent solutions are used to mitigate the condensate damage and improve gas production for the long term. Several laboratory measurements were carried out to study the performance of the proposed approach; coreflooding, zeta potential, and nuclear magnetic resonance (NMR) experiments were conducted. The chemicals were injected into the tight rocks to recover the condensate and improve the flow conductivity. Zeta potential was performed to assess the rock wettability before and after the chemical injection. Moreover, the changes in pores network due to the chemical treatments as analyzed using the NMR technique. Thermochemical treatment removed around 66% of the condensate liquid, while the chelating agent reduced the condensate saturation by around 80%. The main mechanism for condensate removal during thermochemical flooding is the generation of micro-fractures that increase the rock permeability and improve the condensate flow. On the other hand, chelating agents can alter the rock wettability toward less oil-state, leading to considerable recovery of the condensate liquid utilizing a wettability alteration mechanism. Finally, an integrated approach is suggested to injecting thermochemical fluids followed by chelating agent solutions. The proposed technique can lead to generating micro-fractures of less oil-wet surfaces, consequently, the condensate bank can be removed by more than 90%.
A Comprehensive Study Developing and Maximizing the Recovery of Gas Condensate from a Giant Onshore Abu Dhabi Gas Field Utilizing Advanced Condensate Tracking, Gas Injection and Drilling Strategies in Next-generation Commercial Numerical Simulator
Authors: Bernadi Bondan , Mohamed Ihab Nabil , Bairaq Ahmed Mohamed Al , Hosani Mariam Ahmed Al , Abdullayev Azer , Roopal Allen
Published: December 2021

A comprehensive study of a giant onshore Abu Dhabi gas field using a next-generation commercial numerical simulator has been conducted. The objective was to identify the distribution and track the movement of the gas condensate in the reservoir, and to develop strategies to minimize the condensate drop-out and improve condensate recovery from the field.

The field contains a large gas cap and an oil rim. We have identified the distribution of the gas condensate throughout the reservoir and were able to track its movement using the advanced fluid tracking option in the simulator. Once the gas condensate drop-out regions in the reservoir are identified, sensitivity runs with localized changes are carried out to improve the recovery from the reservoir. The strategies to mitigate drop-out include adding infill wells, drilling multi-lateral wells, reinjecting CO2 and dry gas into the reservoir, and hydraulic fracturing near the well bore.

We were able to track the distribution of the condensate throughout the reservoir and identified key condensate drop-out regions. Adding infill wells improved the recovery of the condensate. Implementing multi-lateral wells also showed improved condensate recovery in the field. Hydraulic fracturing near the wellbore reduced condensate banking near the wellbore. Injecting dry gas improved the condensate recovery by a re-vaporization process where the liquid condensate is absorbed by dry gas.

This paper discusses a comprehensive study on tracking the condensate distribution in a giant onshore field using a commercial simulator. The authors have performed a thorough investigation to identify an optimal condensate recovery strategy for the field, by comparing various recovery strategies using the full field reservoir simulation model.
Cost-Efficient De-Bottlenecking of Produced Water Treatment Systems through the Application of a Single Technology, Eliminating the Need for Hydrocyclones and Degassing Drums
Authors: Asdahl Steinar , Jansen van Rensburg Johann , Waag Martin Einarson , Glenna Nilssen Rune
Published: December 2021

Traditionally, produced water from production separators is handled by multiple steps and different technologies in order to meet the required quality for either discharge or reinjection of the water.

The development of the latest Compact Flotation Unit (CFU) technology has unlocked the potential for savings on cost, complexity, footprint and weight for the produced water treatment system.

The developed CFU technology has proven applicable through field testing as a single treatment technology for reducing Oil-in-Water (OiW) content directly from tie-in at separator and still meet stringent requirements for outlet OiW quality.

Field tests were conducted with inlet OiW concentration ranging from 200-2000 ppm, achieving results in the range 2.5 to 21 ppm only with a two-stage latest generation CFU.

Compared to a traditional produced water system setup consisting of de-oiling hydrocyclones and a horizontal degassing vessel, the savings in footprint and operational weight is estimated to 54 % and 53 % respectively utilizing a two-stage CFU for a system with a design capacity of 76.000 BWPD.

Furthermore, the development of the latest generation CFU technology has enabled the retrofit concept, incorporating the developed CFU internals into existing gravity separation based produced water vessels, converting them to more efficient flotation vessels with increased capacity. For brownfield and debottlenecking applications, operators are challenged by increasing water cut from maturing wells, and as a result exceeding the facilities design capacity for produced water treatment. This challenge is often further reinforced by increasingly stricter environmental legislation for OiW content for discharge or re-injection. The retrofit concept will offer a highly cost-, footprint- and weight-efficient solutions to these challenges utilizing existing vessels.

Benefits of the retrofit concept: Bring proven and unique performance of the technology to other produced water separation vessels helping the operators improve the separation efficiency and increase throughput while meeting discharge requirementsShort execution time compared to installation of new process equipmentLow cost compared to installation of new process equipmentUtilization of existing equipment saves valuable footprint.
Migration to Cased Hole Petrophysics: Are We Ready?
Authors: Bustos Ulises , Duran Carlos , Duarte Alexander , Salguero Alfonso , Vasquez Yira , Chapellin Alvaro , Quinapallo Erika
Published: December 2021

In the present Oil & Gas business context, the uncertainties reduction for hydrocarbon production increase in an operational costs and risk reduction scheme, are among the main drivers in several operating companies in the northern region of South America (Colombia & Ecuador). Electrical logging and drilling tools stuck events due to differential pressures, fishing operations, high wellbore tortuosity, difficult geometries and unconsolidated formations affecting wellbore stability, are among the main problems increasing non-productive time and operating costs. Minimizing open hole operations with a full migration to cased hole data acquisition, providing inputs for petrophysical uncertainty reductions without jeopardizing well completion decisions or initial reservoir characterization, would constitute an attractive solution for operators. Following those initiatives, we start by achieving a complete open hole formation evaluation and then migrating to case hole data acquisition and petrophysical assessment while benchmarking against open hole results. Low and variable formation water salinity, complex mineralogy's affecting resistivity and radioactive minerals, are common petrophysical challenges in our reservoirs. We had to implement Archie and salinity-independent formation evaluation solutions with cased hole technologies and in absence of open hole logs.

The open hole petrophysics consist on simultaneous assessment of matrix and fluids saturations, while evaluating the oil mobility and water cut with the incorporation of multi-depth of investigation sensors in single logging runs (spectroscopy, dielectric dispersion, and magnetic resonance). We then moved to cased hole formation evaluation, with spectroscopy & nuclear-based petrophysics in gas, light oil, and heavy oil-bearing reservoirs. By implementation of non-archie fluids volumetric computation (that relies on conversion of dry weight total carbon to oil saturation and fast neutron cross section to gas saturation- done through a simultaneous inversion by solving matrix-porosity-fluids volumes into an elemental analysis), we obtained a representative formation saturation range behind casing. We then discussed on the different scenarios were migrating to cased hole is sustainable and its potential limitations.
Geo-Thermo-Mechanical Modeling of Pre-Drilled Wellbores to Extract Geothermal Energy from Subsurface to Produce Cleaner Energy for United Arab Emirates
Authors: Ansari Ubedullah , Soomro Najeeb Anjum , Narejo Farhan Ali , Baloch Shafquat Ali , Talpur Faiz Ali
Published: December 2021

The middle eastern countries including United Arab Emirates (UAE) have enjoyed the energy production from hydrocarbon resource for a very long period. Indeed, now various countries in this region has shifted to alternative resources of power generation with cheaper and cleaner sources. Geothermal is the top of the list among those sources. Therefore, this study presents an ultimate model converting abandoned oil and gas wells into subsurface geothermal recovery points.

Fundamentally, this study offers a geo-thermo-mechanical model of abandoned wellbore which can help in developing an optimistic geothermal energy not only from subsurface thermal reserve but also from abandoned casing and pipes installed in Wellbores. In this approach the source of heat is thermally active rock formations and the metallic pipes that are present in wellbores drilled through hot dry rocks. In the model the already drilled wells are incorporated as medium of heat flow in which water in injected and brought back to surface along with thermal impact.

The results of this study revealed that, at the depth of 6000 m of high temperature wellbore the temperature is above 85°C and at this temperature the metallic casings further rise the reserve temperature thus the conversion of water into steam can be processed easily. Moreover, at high depths the stability of wellbore is also issue in high temperature formation, so mechanical model suggests that injection of water and conversion into steam in already cased wellbore can sustain up to 6 MPa stress at around 100C. Thus, the geo-thermo-mechanical model of wellbore will illustrate the possibility of converting water into steam and it will also reveal the average amount of heat that can be generated from a single well. henceforth, the thermal recovery from abandoned wells of UAE is best fit solution for clean energy.

The abandoned wells are used as conduit to transport heat energy from subsurface by using water as transport medium, as water at surface temperature is injected in those wellbores and let thermal energy convert that water into steam. Later the steam is returned to surface and used as fuel in turbines or generators.
Using Seismic Data to Predict Shale Pore Pressure and Overpressure Sweet Spots: A Case Study from the Lower Silurian Longmaxi Formation in Sichuan Basin, China
Authors: Chen Sheng , Zeng Qingcai , Wang Xiujiao , Yang Qing , Dai Chunmeng , Li Wenke , Jiang Ren
Published: December 2021

Practices of marine shale gas exploration and development in south China have proved that formation overpressure is the main controlling factor of shale gas enrichment and an indicator of good preservation condition. Accurate prediction of formation pressure before drilling is necessary for drilling safety and important for sweet spots predicting and horizontal wells deploying. However, the existing prediction methods of formation pore pressures all have defects, the prediction accuracy unsatisfactory for shale gas development. By means of rock mechanics analysis and related formulas, we derived a formula for calculating formation pore pressures. Through regional rock physical analysis, we determined and optimized the relevant parameters in the formula, and established a new formation pressure prediction model considering P-wave velocity, S-wave velocity and density. Based on regional exploration wells and 3D seismic data, we carried out pre-stack seismic inversion to obtain high-precision P-wave velocity, S-wave velocity and density data volumes. We utilized the new formation pressure prediction model to predict the pressure and the spatial distribution of overpressure sweet spots. Then, we applied the measured pressure data of three new wells to verify the predicted formation pressure by seismic data. The result shows that the new method has a higher accuracy. This method is qualified for safe drilling and prediction of overpressure sweet spots for shale gas development, so it is worthy of promotion.
Petroleum Development Oman Forecasting Management System
Authors: Al Riyami Hilal Mudhafar , Al Sheibani Hilal Mohammed , Al Subhi Hamed Ali , Al Ajmi Hussain Taqi , Zohny Zeinab Youssef , Al Kindy Azzan Qais
Published: December 2021

Production performance forecasting is considered as one of the most challenging and time consuming tasks in petroleum engineering disciplines, it has important implications on decision-making, planning production and processing of facilities. In Petroleum Development Oman (PDO), which is the major petroleum company in Oman, production forecast provides a technical input basis for the economic decisions throughout the exploration and production lifecycle. Reservoir engineers spend more than 250 days per year to complete this process. PDO Forecast Management System (FMS) was introduced to transform the conventional forecasting of gas production. Employing the latest state-of-the-art technologies in the field of data management and machine learning (ML), PDO FMS aims at optimizing and automating the process of capturing, reporting, and predicting hydrocarbon production. This new system covers the full forecast processes including long and short-term forecasting for gas, condensate, and water production. As a pilot project, PDO FMS was deployed on a cluster of 272 wells and relied on agile project management approach to realize the benefits during the development phase. Deployment of the new system resulted in a significant reduction of the forecasting time, optimization of manpower and forecasting accuracy.
Intelligent Fracture Diagnostic Procedure Using Smart Microchip Proppants Data
Authors: Van Pham Vuong , Kalantari Dahaghi Amirmasoud , Negahban Shahin , Fincham William , Babakhani Aydin
Published: December 2021

Unconventional oil and gas reservoir development requires an understanding of the geometry and complexity of hydraulic fractures. The current categories of fracture diagnostic approaches include methods for near-wellbore (production and temperature logs, tracers, borehole imaging) and far-field techniques (micro-seismic fracture mapping). These techniques provide an indirect and/or interpreted fracture geometry. Therefore, none of these methods consistently provides a fully detailed and accurate description of the character of created hydraulic fractures. This study proposes a novel approach that uses direct data from the injected fine size and battery-less Smart MicroChip Proppants (SMPs) to map the fracture geometry. This novel approach enables direct, fast, and smart of the received high-resolution geo-sensor data from the SMPs collected in high pressure and high-temperature environment and maps the fracture network using the proposed Intelligent and Integrated Fracture Diagnostic Platform (IFDP), which is a closed-loop architecture and is based on multi-dimensional projection, unsupervised clustering, and surface reconstruction. Affine transformation and a shallow ANN are integrated to control the stochasticity of clustering. IFDP proves its efficacy in fracture diagnostics for 3 in-house design synthetic fracture networks, with 100% consistency, rated "fairly satisfied" to "highly satisfied" in prediction capability, and between 85-100% in execution robustness. The integration of the couple affine transformation-ANN increases the performance of unsupervised clustering in IFDP.
Production and Quantification of Virulence Factors in Malassezia Species
Authors: Hadrich Inès , Neji Sourour , Trablesi Houaida , Ilahi Amin , Chouaki Taieb , Ranque Stéphane , Makni Fattouma , Ayadi Ali
Published: December 2021

A total of 77 strains of Malassezia were included in this study. Biofilm production and hydrolytic enzymes were studied by using specific solid media. Real-time Reverse Transcriptase qPCR method was applied to determine overexpression of genes encoding extracellular enzyme.
All included Malassezia species produced biofilms. No statistical significant difference was observed between biofilm formation of the Malassezia species (P = 0.567) . All Malassezia species produced lipase and 95% of M. globosa showed a strong enzymatic activity (Pz=0.55 ± 0.02). Statistical significant difference was observed between the mean keratinase indices of M. slooffiae and the others Malassezia species ( P = 0.005).
The overexpression of one or more genes was observed in 100% of strains isolated from patients with folliculitis, in 87.5% for pityriasis versicolor isolates and in 57.14% for the control group isolates. A statistical significant difference of the lipase gene expression ( P = 0.072) was associated with the strains collected from patients with folliculitis vs group control.
This investigation provides more information about the frequency of the production of the major enzymes considered to be virulence factors of Malassezia species. Interestingly, the overexpression of one or more genes was observed in strains isolated from patients with Malassezia disorder.