bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a Completion Model for the Monitoring of EOR in Wells with Heavy and Extra Heavy Crude in the Largest Deposit in Latin America
Authors: Pena Gerardo , Patiño Deivy 
Published: March 2019

Abstract
To validate the completion model, a computer simulation was performed in four scenarios to predict mechanical failure limits. Consequently, a completion design model was obtained using vacuum-insolated tubing (VIT) that enables a minimum of 75% of steam quality given an inlet steam quality of 80%. In addition, a seal bore is used at 50° to 60° of inclination, which enables the upper completion disconnection/connection through the seal stinger at that depth, without losing production capabilities for changes in the depth of top of connection of tie-back. This paper describes the type of completion development and challenges encountered during the design. The advantages and benefits of collecting the correct information in the process of thermal recovery in the joint venture are also discussed.
The investigation resulted in a completion model of thermal wells that will enable the monitoring of the conditions of the injection, tubing, casing, and injection effectiveness in the system in which the cyclic process is applied and adjusted to wells in the Orinoco Belt. A conclusion of this investigation is that, during the injection, the movement of production string and the monitoring component must be independent to avoid the transference of stress resulting from thermal expansion. Polished bore receptacles and seal assemblies should be used in the replacement of expansion joints; this will enable the upper completion to be used for recovery and changed for the injection system.
Although completion models have been developed in which the steam path can be monitored, they have not been developed previously for use in long horizontal section wells, as was performed in this case. The problem of thermal expansion of the tubing during steam injection is expected to be resolved with the implementation of the design based on this study. Feed-through packers have already been developed especially for this process, although with a mixed record of successful and unsuccessful deployments. The monitoring system must be mechanically independent of the injection system, such that movements associated with expansion and contraction do not have a significant effect.
Verification of a CFD-Population Balance Model for Crude Oil Separation Efficiency in a Three-Phase Separator – Effect of Emulsion Rheology and Droplet Size Distribution
Authors: Oshinowo Lanre , Vilagines Regis 
Published: March 2019

Abstract
In this study, a multidimensional computational fluid dynamics (CFD), combined with the Population Balance Model, is used to predict the gas, oil, and water separation behavior in a horizontal three-phase high-pressure, high-temperature pilot separator at different flow rates and water cuts, and predict the thickness of the dense packed emulsion layer above the water interface. The multi-fluid Eulerian multiphase model, coupled with a multivariate population balance model, is applied to predict emulsion destabilization and separation, and validated with experimental data. The population balance model is applied to predict the changing droplet size distribution in the crude oil emulsion due to droplet coalescence. The effect of water cut on the emulsion rheology was incorporated in the CFD model to predict the existence of the dense packed layer or zone (DPZ) – a high water-cut emulsion layer formed at the interface between the oil and water phases. A novel emulsion viscosity model incorporates a dependence on the local droplet size. The CFD modeling predicts the flow patterns and phase distributions throughout the separator, and the dispersed water droplet size distribution in the emulsion/liquid phase. Parameter estimation for the droplet coalescence kernel in the population balance equation is determined from experimental measurements of emulsion separation kinetics. A Proportional Integral Derivative (PID) controller logic is used to maintain the gas/oil and oil/water interface levels by automatically adjusting the oil and water outlet pressure, respectively. Experimental data from a high-pressure pilot scale separator is compared to the predicted phase flow rates into and out of the vessel, and vertical phase profiles to CFD results. The CFD model reproduced separation efficiency, three-phase distribution and the DPZ influence on oil-water separation efficiency and demonstrates an effective methodology to evaluating full-scale separator performance.
Advances in Rock Petrography: Image Processing Techniques for Automated Textural Thin Section Analysis
Authors: Mokhles Mezghani , Fatai Anifowose , Mohammed Masrahy 
Published: March 2019

Abstract
Point counting is time consuming and requires extensive geologist/petrographer effort. In addition, point counting results are subjective and depend on the petrographer's knowledge and expertise. In this work, we introduce a fully automated workflow for thin section textural analysis in clastic rocks, using high resolution petrographic images of the thin sections acquired with a digital camera mounted on an optical microscope. This innovative workflow reduces the thin section textural analysis turnaround time and provides an objective and consistent analysis.
The strength of this workflow resides in its high level of automation, which offers thin section analysis tool in much less time compared to the conventional point counting. The workflow is fully automated to process and analyze the entire thin section without manual involvement. The kernel of this workflow is based on a region growing algorithm for individual grain identification. An iterative loop, built on the top of this kernel, allows the completely automated scan of the entire thin section.
The workflow was first rigorously validated for a single thin section. Grain by grain, results from the automated analysis are compared to the petrographer (point counting) analysis. Excellent agreement between the two analyses was obtained (porosity and grain size). The efficiency of the analysis was largely in the favor of the automated approach (3 minutes) compared to the 2 hours needed by the petrographer for this counting exercise (approximately 150 grains). This first validation test proved the workflow's accuracy and the efficiency.
This workflow was then extensively validated using large set of thin sections (50 thin sections) showing an excellent qualitative agreement with conventional point counting. This second validation test proved the robustness and the efficiency of the workflow.
Isotopic Characterization of Formation Waters: Applications and Challenges
Authors: Lu Feng , Harthi Owaidh , Dubaissi Jaffar 
Published: March 2019

Abstract
Formation waters contain important information including the source, reservoir connectivity, and geological/biogeochemical processes, which can be used to aid work associated with petroleum exploration and production. Such information can be obtained by conducting geochemical analyses of water. Isotope technology is one of powerful geochemical tools and has been well applied to characterize formation waters. There are challenges to apply isotope technology. For example, petroleum formation waters commonly contain high total dissolved solids (TDS) and petroleum compounds, which can have a huge impact on the quality of stable H- and O-isotope analyses. Here we present an innovative methodology dealing with high quality of isotope analysis of formation waters, which contain abundant petroleum compounds and high TDS. The most widely used method of analyzing oxygen isotopes in water involves pure CO2 gas interaction with the targeted water for twenty-four hours, and then measure O- isotopes of CO2. However, some studies have indicated that the exchange rate of oxygen isotopes between CO2 and water highly depends on the amount of TDS in water. Experimental work in this study indicates that the established period of time (24 hours) is too short to reach isotope equilibrium between CO2 gas and typical petroleum formation waters, which commonly have a high TDS. This study shows that waters with different ranges of TDS require different periods of time for water-CO2 interaction to reach an isotope equilibrium. In addition, experimental work has shown that petroleum compounds dissolved in formation water have gravely affected the quality of both O- and H-isotope analyses. Experimental work of removing petroleum compounds was conducted, and the effective processes have made it possible to successfully achieve the high quality of isotope analysis.
Artificial Neural Network ANN Approach to Predict Fracture Pressure
Authors: Ahmed S Abdulmalek , Elkatatny Salaheldin , Ali Abdulwahab Z , Abdulraheem Abdulazeez , Mahmoud Mohamed 
Published: March 2019

Abstract
Fracture pressure is a critical formation condition that affects efficiency and economy of drilling operations. The knowledge of the fracture pressure is significant to control the well. It will assist in avoiding problems associated with drilling operation and decreasing the cost of drilling operation. It is essential to predict fracture pressure accurately prior to drilling process to prevent various issues for example fluid loss, kicks, fracture the formation, differential pipe sticking, heaving shale and blowouts.
Many models are used to estimate the fracture pressure either from log information or formation strengths. However, these models have some limitations such as some of the models can only be used in clean shales, applicable only for the pressure generated by under-compaction mechanism and some of them are not applicable in unloading formations. Few papers used artificial intelligence (AI) to estimate the fracture pressure. In this work, a real filed data that contain only the real time surface drilling parameters were utilized by artificial neural network (ANN) to predict the fracture pressure.
The results indicated that artificial neural network (ANN) predicted the fracture pressures with an excellent precision where the coefficient of determination (R2) is greater than 0.99. In addition, the artificial neural network (ANN) was compared with other fracture pressure models such as Matthews and Kelly model, which is one of the most used models in the prediction of the fracture pressure in the field. Artificial neural network (ANN) model outperformed the fracture models by a high margin and by its simple prediction of fracture pressure where it can predict the fracture pressure from only the real time surface drilling parameters, which are easily available.
Using Data Driven Analytical Models with Compositional Simulation in Doubling the LPG Production from Bahrain Field
Authors: AlMuftah Ali , AlOwainati Ebrahim , Mansoor Mohamed 
Published: March 2019

Abstract
Crestal gas injection started in the Bahrain Field in 1938 and since then, 1,900 Bscf has been injected in Mauddud, the main oil producing reservoir in the Bahrain Field, creating a secondary gas cap. Furthermore, since 1965, an estimated 100 MMstb of Liquefied Petroleum Gas (LPG), or 14% of the bypassed oil, has been recovered from the secondary gas cap through stripping with the remaining oil volume in the secondary gas cap being approximately 700 MMstb. Today, the remaining oil saturation in the Mauddud gas cap is estimated to be approximately 40%.
This paper presents the results of an extensive study that was made to forecast the Bahrain Field associated gas compositions and potential gas-liquids production recovery. Several forecast methodologies were used including data-driven analytical models, a compositional cross-section model, and a full-field compositional history matched model. The results of these forecasts and the conclusions are presented and compared. In this study, two scenarios of different gas compositions of injected gas and their impact on gas plant liquids recovery are explored.
In addition, this paper addresses the challenges and uncertainties associated in forecasting the gas compositions and ways to overcome them. The data-driven models and compositional cross-section model were initially used, however, due to their inherent uncertainties, a full field compositional simulation model was necessary. This compositional model was history matched with a seven (7) component Equation of State (EOS) to capture the lighter hydrocarbon components. Moreover, this model was used in predicting the yield and composition of the existing gas recovery plant. The results from all methods recommend doubling the capacity of the existing plant, which was commissioned in late 2018. A comparative analysis found that data-driven models can be used for gas cycling when using the same gas injection compositions. However, data-driven models over-estimate the Liquefied Petroleum Gas (LPG) yield if leaner gas is used for gas injection, which is the case for the proposed gas plant expansion.
First Worldwide Application of HP/HT Water Swellable Packers Eliminates Deployment Risks and Improves MSF Efficiency in Tight Gas Reservoirs
Authors: Arias Rommel E. , Guizada Pablo , Mohanna Khalid Al , Desai Ankur 
Published: March 2019

Abstract
This paper presents the first-time application of high pressure/high temperature (HP/HT) water swellable packers worldwide for multistage fracturing completions. This technology eliminates deployment risks associated with premature swelling in high temperature oil-based muds (OBM) and improves efficiency of fracturing operations in tight gas reservoirs.
The overall deployment method of this technology is similar to traditional open-hole multistage fracturing technologies that are industry standard. The main difference being that the isolation packer used is an HP/HT water swell packer that uses water/brine as the swelling medium as opposed to hydrocarbon. The technology comprises of an innovative compound that is capable of holding high differential pressure at high reservoir temperatures and maintaining permanent isolation in a relatively compact element length. The elastomer compound completed an extended qualification process to ensure fulfilling deployment and fracturing completion requirements in a specific well candidate.
The outcome was an overall successful deployment and stimulation operation of multi stage completion with HPHT water swell packer technology. Water swell packer provided the ability to deploy the lower completion in high temperature/OBM environment with a significant increase of swelling factor delay and its compact length reduces stiffness in the BHA to further decrease the deployment risk. In addition, this technology provided an optimization technique for open-hole multi-stage stimulation by circulating out the drilling mud and leaving completion brine in the wellbore and annular space. Through a complete diagnostic process, it was confirmed that the water swellable packers successfully isolated each stage of the stimulation treatment.
Prior to the first worldwide installation of an innovative elastomer compound, unique testing was conducted in the laboratory and in field tests to qualify the compound technology with special focus on the acid stimulation treatments domain. The elastomer compound was made of special fillers to chemically retain water in the elastomer matrix and eliminate any reverse osmosis problem present in traditional water-swellable compounds.
Deployment and Detection of a Novel Barcoded Advanced Tracers System for the Optimization of Improved Waterflood Recovery in Hydrocarbon Reservoirs
Authors: Thomas Gawain , Ow Hooisweng , Chang Sehoon , Shi Rena , Wang Wei , Chen Hsieh , Poitzsch Martin , Shateeb Hussain , Abdel-Fattah Amr 
Published: March 2019

Abstract

Objectives/Scope
A novel barcoded advanced tracers system has been developed and field-validated in a hydrocarbon reservoir. With a detection scheme that supports automation, this cost-effective tracers system is designed to enable potentially ubiquitous long-term full-field injections in the interest of using the high fidelity tracer data to increase the oil recovery factor through improved optimization of the water injection and oil production.

Methods, Procedures, Process
Our Advanced Tracers system uses real-time chromatographic separation and optical detection to achieve ultra-low limits of detection (LOD) at 1 part per billion (ppb) or better. Such low LOD facilitates small injection quantities, making full field deployment of Advanced Tracers cost-effective compared to state-of-the-art interwell tracers. Additionally, the detection strategy that enables automation of the analysis process for real-time tracer detection is outlined, paving way for minimal manual sample collection and work-up.

Results, Observations, Conclusions
Results on recently field-validated real-time optically-detectable tracers in a hydrocarbon reservoir, detectable at ultra-low LODs, are described. This is achieved even in the presence of background oil by means of an intrinsically oil-blind detection method. The material exhibits high mobility in high-salinity high-temperature carbonate reservoirs, with tracer breakthrough successfully detected at concentrations of less than 1 ppb using chromatographic separation followed by an optical detection method. The novel methodology as outlined highlights its simplicity, safety and cost-effectiveness relative to current practices in the field.

Novel/Additive Information
Fluorobenzoic acid based tracer technology requires chemical derivatization of the samples for ultra-low detection limits in a GC-MS. Our novel tracer detection strategy omits the need for chemical derivatization. In addition, it enables a compact, portable, optical-based automated wellsite detection system to be used in the field, with tens of unique barcodes possible. These innovative steps are keys to near real-time tracer detection in the field, realizing one of the intelligent oil field monitoring and the reservoir management applications.
The Development of a Novel Log Based Permeability Transform for a Mature Carbonate Reservoir and its Significance in Explaining the Water Flood EOR Response
Authors: Dowen Michael , AlAli Abdulkarim , Nemmawi Nadia 
Published: March 2019

Abstract
The unexpected response of the Mauddud water flood project led to a detailed review of the petrophysical and geological aspects of this mature cretaceous carbonate reservoir. With almost 2,000 wells, more than 1,000 of which were recently drilled and three cored, the review assessed an extensive data base of open-hole, production, saturation log, and historical geological data.
The findings resulted in an improved understanding of this reservoir, which historically had been described both as homogenous - fractured and heterogeneous – layered. An understanding of Mauddud's key geological features, their formation, and a link to the observed petrophysics provided the key to developing an innovative permeability transform from resistivity logs, which explained the reservoirs response to the water flood project.
With production permeability up to fifty times the measured matrix permeability from core, porosity log derived permeability had failed to reflect the fluid production observed. The adoption of a saturation and production based method provided a useable permeability profile that appeared to explain the observed well and pattern production behavior of the water flood. The new permeability profile also explained both historical fluid behavior and other Enhanced Oil Recovery (EOR) projects, and has since been universally adopted for the reservoir.
The permeability estimation technique, which uses resistivity log data, was tested in another in-field reservoir with success, and it is thought that the technique has general applicability across many Middle East carbonate reservoirs.
Improving Efficiency and Accuracy in Estimating Well Potential Using an Integrated Asset Operations Model
Authors: Cornwall Rachelle Christine , Mubarak Al Nuimi Saber , Tripathi Deepak , Hidalgo Melvin , Soni Sandeep 
Published: March 2019

Abstract
This paper describes an efficient approach for estimating well potential using advanced, automated workflows for a large field with more than a thousand well strings from multi-layered reservoirs having different characteristics. This paper provides insight into reservoir guidelines, well performance, and surface facility constraints using the integrated asset operations model (IAOM) to compute well potential.
The IAOM tool automates an engineering approach in which reservoir management guidelines, in conjunction with calibrated wells and a network model, are used to estimate well potentials. This process incorporates the interaction among various components including wellbore dynamics (Inflow performance and well performance), surface network backpressure effects and well performance key parameters, such as GOR and water cut. This engineered workflow computes the well potential corresponding to each guideline and constraint.
This engineered workflow has reduced the time to compute the well potential rate from 3-4 weeks to just 2 hours for this large field, reducing computation time by more than 95%. This workflow helped engineers to avoid tedious manual calculations on a well-by-well basis and allowed them to focus on engineering, analytical, and optimization problems. The confirmation of calculated well potential rates using the updated surface network model helped in finalizing the business scenarios such as field-capacity tests. For example, the accuracy of predicted results in a zonal capacity test was approximately 98% using this engineered workflow approach. The value derived from this engineering logic using validated physical models supported the business plan and further identified key candidates for production optimization without heavy dependence on drilling additional wells, leading to cost optimization. This automated workflow ensures the use of updated physical models and maintains higher accuracy of results. This digital system-based data-management process supports data governance objectives.
This enhanced workflow supports corporate objectives of standardization for a work process to set well allowable, in line with the operator's integrated reservoir management (IRM) initiative.
Geological Modelling of the Enjefa Beach Marginal Marine Outcrop; A Comparison Between Holocene and Cretaceous Tidal Channel Complexes
Authors: Amer Aimen , Al-Wadi Meshal , Salem Hanan , Sajer Abdulazziz , Al-Hajeri Mubarak , Najem Ali 
Published: March 2019

Abstract
Outcrop work represents the main source of analogs used to model subsurface reservoirs. Without such explanation of reservoir geometry, architecture, and characterization, producing subsurface formations would be largely uncertain. The aim of this paper is to build a geological static model for the Enjefa Beach outcrop exposed in Kuwait and use it to better understand subsurface reservoir architectures. This was achieved by acquiring several traverses along the outcrop, describing the various rock units, and understanding the depositional facies and facies associations. The next stage was to model each depositional unit as a separate zone embedded in an integrated model. This was followed by developing a forward synthetic three-dimensional seismic model to better understand how such reservoir architecture may appear in the subsurface. The final step was to use these findings in modeling a subsurface Cretaceous reservoir in northeastern Kuwait. The resultant model demonstrated that detailed geological complexities can be captured by conventional modeling techniques; in the model, the middle shoreface, upper shoreface, foreshore, and tidal channel complexes were statically modeled. Subsurface seismic data showed a series of highly sinuous meandering channels. Stacking patterns were found to vary among vertical, climbing, and compensational stacking patterns.