bluuebunny/crossref_metadata_2025_split huggingface dataset:
High Definition Reservoir Mapping Technology Provides a Unique Solution to Map Uncertain Water Contact as an Innovative Approach for Pilot Hole Elimination; Umm Ghudair Field, West Kuwait
Authors: AL-Hajri Nasser Fadghoush , Al-Khaldy Ali Dawood , Hassan Jassim Mohammed , Dashti Reham Abbas , Kader Mohamed Abdulmonem , Gupta Satya Kumar , Al-Buloushi Zainab Abdulkareem , Abdelbaset Shady Moustafa , Siam Mahmoud , Al-Hassan Ahmed , Chang Catherine , Ramadan Zeyad 
Published: June 2020

Abstract
Umm Ghudair Field is one of the major oil producing fields in West Kuwait. Oil was discovered in 1962 in the Lower Cretaceous Minagish Oolite Formation and more than 200 wells have been drilled to exploit this reservoir since then. Stratigraphically, the formation is defined by three units; Lower, Middle and Upper. The lower and upper units are considered non-reservoirs, while the middle one is hydrocarbon bearing. However, because of the continuous production over the past 50 years, the filed started to show a variable rise in its oil water contact (OWC). Consequently, this uncertain OWC rise has impacted the planning and production of the newly drilled wells (deviated and horizontal). Several recently drilled wells showed water breakthrough much earlier than expected.
To address this challenge and with an attempt to proactively predict the current OWC depth in the new wells to be drilled, Kuwait Oil Company (KOC) decided to try the new High Definition Reservoir-Mapping-While-Drilling (HD-RMWD) technology in one of the horizontal well in their field. The objective was to assess the potential of the technology in detecting and mapping the current OWC while landing the well in the target. Due to the ultra-deep detection range of the technology (in excess of 200 ft), the landing point could be adjusted proactively and early enough to accommodate any unexpected OWC depth changes in the field.
Exergoeconomic Optimization of Oil and Gas Production Systems
Authors: Akchiche Meziane , Beauquin Jean-Louis , Sochard Sabine , Serra Sylvain , Reneaume Jean-Michel , Stouffs Pascal 
Published: June 2020

Abstract
In the present paper, we first developed and implemented the exergy analysis within an Integrated Asset Modeling (IAM) platform to evaluate the overall energy efficiency and Greenhouse Gas (GHG) emissions of a future offshore oil production system. The use of the same state function enables a direct comparison of the different irreversibilities that occur through the entire production system (drawdown losses, lift losses, Artificial lift and boosting systems losses, etc.) and thus, provides the necessary guidance for engineers to select the best solution. Then, we modeled and evaluated the performance of the oil production system with three artificial lift and boosting techniques, including multiphase boosting, gas lift, and ESP. In all the cases, liquid production has been maximized while respecting the same constraints. The exergy analysis enabled us to quantify for the first time the physical exergy supplied naturally by the reservoir in the form of pressure (mechanical exergy) and temperature (thermal exergy). After that, we proposed a new methodology to improve the design of petroleum production systems over their whole life. This methodology permits the simultaneous evaluation of a multitude of development schemes by using generic models. Finally, the multi-period exergoeconomic optimization results highlight a performance gap, quite logical, between the most cost-effective scheme identified and the most energy-efficient one. There are hence excellent opportunities for progress by developing the exergy approach and digital tools for the selection and development of greener and more profitable production concepts, processes, and technologies.
Modelling of Multi-Stage Hydraulic Fractured Wells Made Easy in Conventional Reservoir Simulations
Authors: Hoegstoel Haakon , Stoeren Jacob , Sjaastad Magne , Lindkvist Gaute 
Published: June 2020

Abstract
The success in shale oil and gas over the last decade is based on massive multi-stage hydraulic fracturing. Applying the same well concept on conventional tight and low permeable reservoirs can bring economically stranded projects into consideration again. However, simulating production over time for multi-stage hydraulic fractured wells using conventional full-field reservoir simulation models can be challenging. Detailed modelling of the hydraulic fractures comes with a large computational cost and typically a number of convergence issues. Simplified methods fail to capture the full pressure loss from the reservoir into the well. In this work, a method with effective Virtual Perforations is described, enabling both efficient simulation and prediction of well performance. A detailed 2D mesh for each hydraulic fracture is used together with the unmodified reservoir model grid, integrating geomechanical fracture propagation simulation results directly into the reservoir simulation workflow.
The Virtual Perforations are defined by the geometrical intersections between the fractures 2D meshes and the reservoir model 3D grid. The numerical solution of the fracture-to-well inflow system provides a set of effective Virtual Perforations transmissibilities for Darcy flow which can be applied in any standard reservoir simulator. In the reservoir simulation model numerical multipliers, in-active grid blocks or gaps in grid model layers can act as barriers for vertical flow in the fractures. Hence horizontal, fractured wells may not capture the full flow potential in reservoir simulations. In this work, the effective Virtual Perforations are calculated based on the vertical fracture mesh to ensure well flow from the full height of the hydraulic fractures. Using a 2D mesh for the fracture, the fracture geometry can be contained within certain grid model layers or truncated by faults. Matrix condensation methods known from degree-of-freedom reduction in structural analysis, are applied to efficiently calculate all the effective Virtual Perforations transmissibilities. Thus, working with well completion design can be done interactively.
For gas reservoirs, a non-Darcy pressure loss model is established based on the Forchheimer model. Fracture width and proppant inertial flow parameter for a given confinement stress are used to calculate the rate-dependent skin factor for each fracture. The rate-dependent skin factors are provided for the all the Virtual Perforations in such a way that they all get the same additional near wellbore non-Darcy pressure loss.
This work has been implemented in the open-source visualization application ResInsight. The application has been used successfully for well planning in field development projects, including as part of automated workflows for ensembles of reservoir models.
A Rigorous Method for Special Core Analysis SCAL Data Correction in the Presence of Capillary End Effects
Authors: Goodarzian Saleh , Sorbie Kenneth S. 
Published: June 2020

Abstract
One way of obtaining water-oil relative permeability curves is from co-injection (of water and oil) experiments at steady-state (SS) condition. The two-phase Darcy Law can be used to calculate the relative permeability directly only when water saturation is constant along the core. However, the capillary end effect (CEE) causes water accumulation or depletion at the end of the core depending upon the wettability. This work describes an improved method for correcting for this effect by modifying the "intercept method" initially proposed by Gupta and Maloney (2014).
Similar to their work, we again envisage carrying out a steady-state co-injection experiment. For each ratio of water to oil flowrate (F=qwqo), we require experiments at several different total flowrates to be carried out. From each run, we obtain pressure drop across the core and average water saturation inside the core.
We demonstrate mathematically that a plot of pressure difference vs. oil flowrate yields a straight line whose slope gives the oil relative permeability which can be used to calculate water relative permeability. A plot of average water saturation vs. reciprocal of oil flowrate gives a straight line whose intercept is the water saturation associated with the oil/water relative permeability values just obtained. It is necessary to perform the same experiment for at least two values of water and oil flowrates while the ratio is constant since we require at least two points to construct a straight line. The same procedure is used for other values of F to obtain more data points to construct the relative permeability curves. We have also mathematically corrected Gupta and Maloney’s work and other works after them and arrived at a simpler and more rigorous method. The details of how our method builds upon and improves their work will be published in due course (Goodarzian and Sorbie, 2020).
Novel Techniques Enable Successful Gravel Packing of Long Horizontal North Sea Wells
Authors: Firth James Andrew , Hamid Hisham , Saldungary Pedro Martin 
Published: June 2020

Abstract
Open hole gravel packing (OHGP) is one of the primary completion techniques in sandstone reservoirs with sanding tendencies. As companies are becoming more experienced with these operations they are starting to explore the options for completing more challenging wells; including longer open holes and more tortuous trajectories. Conventional techniques have limits when it comes to the maximum length and angles that can be gravel packed based on a defined set of parameters. In order to ensure the success of the gravel packing operations in these challenging wells new techniques need to be adopted.
This paper includes a review of the methods that can be utilised to extend the operating limits of open hole gravel packs, so that they can be used in the long geosteered wells that are becoming more common in the North Sea. It includes a case review of the first well gravel packed in the North Sea using Ultra-Lightweight (ULW) proppant, which was also the first ever combined use of ULW proppant and diverter valves. These technologies were required due to the long interval length, 4,880ft, and high angle, maximum 103°. A history match of the gravel pack model was also performed to evaluate the performance of the ULW proppant during a long horizontal gravel pack.
Data Driven Machine Learning Models for Shale Gas Adsorption Estimation
Authors: Wang Lei , Liu Mingliang , Altazhanov Arlybek , Syzdykov Bekassyl , Yan Jiang , Meng Xin , Jin Kai 
Published: June 2020

Abstract
Accurate calculation of adsorbed shale gas content is critical for gas reserve evaluation and development. However, gas adsorption and desorption experiments are expensive and time-consuming, while physics-based models and empirical correlations are unable to accurately capture the adsorption characteristics for different shales. Langmuir adsorption is one of the most commonly used model for calculating the adsorbed gas content in shale gas reservoirs. However, most existing correlations for the Langmuir pressure and Langmuir volume in the model are oversimplified based on limited experimental data points. Thus they are not representative of key geological parameters and are far from accurate for prediction in many cases. We developed a variety of machine learning models that are multivariable controlled to quantify shale gas adsorption.
The data-driven method subdivides into two procedures: data compilation and machine learning regression. Over 700 data entries, composed of reservoir temperature (T, °C), total organic carbon (TOC, wt%), vitrinite reflectance (Ro,%), Langmuir pressure, and Langmuir volume are compiled from shale gas plays mainly in USA, Canada, and China. Data have been consistently curated, then machine learning approaches, including multiple linear regression (MLR), support vector machine (SVM), random forest (RF) and artificial neural network (ANN), have been built, trained and tested by partitioning the data into 75%:25%. For SVM, RF and NN models, 1000 simulations were run and averaged for performance comparison.
MLR identifies non-negligible parameters and general trends for shale gas adsorption. Nonetheless, the correlation coefficients from MLR are far from satisfactory. For Langmuir pressure, RF models fit best to the data entries and the other models follow the order of SVM &gt; ANN &gt; MLR. Particularly, RF models show the highest performance stability with the averaged R-squared value of 0.84 and the maximum of 0.87, indicating a very strong relationship constructed for these 213 data entries. For 485 Langmuir volume data entries, RF models also perform best while the other three regression methods are comparable. It should be noted that altering machine learning model structure and parameters could significantly affect the regression results.
Robust and universal machine learning models for estimating adsorbed shale gas content with high confidence level are established, which not only provide more accurate estimation and broader parameter adaptation than physics-based and empirical models, but also circumvent the high-cost and time-consuming deficiency of experimental measurements. These machine learning models can be used to estimate adsorbed gas content for shale plays with limited experimental measurements. Moreover, they can be incorporated into reservoir simulators to improve the simulation performance.
Quantifying the Importance of Decisions and the Impact of Data Acquisition on Decisions in Hydrocarbon Field Re-Developments
Authors: Steineder Dominik , Clemens Torsten 
Published: June 2020

Abstract
Hydrocarbon field (re-)development projects require the evaluation of a large number of development options under uncertainty. Furthermore, information of data gathering programs might result in narrowing parameter ranges and change the choice of the preferred development option.
The large number of development options (and decisions accordingly) which have to be taken under uncertainty leads to the necessity to determine the impact of the decisions on the (re-)development project objective. Knowing the sensitivity of the decisions on the project objective (e.g. NPV) allows for resource and data acquisition planning. The impact of decisions on the project value can be determined by performing a Generalized Sensitivity Analysis. This analysis does not replace Value of Information but facilitates planning and allows focusing on important decisions.
To further improve Decision Analysis and focus on important parameters, a Generalized Sensitivity Analysis of uncertain parameters on decisions can be performed. The advantage of such an investigation over sensitivity analysis on Oil Originally in Place (OOIP) or Net Present Value (NPV) is that it includes parameter interactions. Furthermore, it covers the impact of a parameter on the decisions directly rather than indirectly when OOIP or NPV sensitivity is used.
The analysis is shown at an example project in a Decision Analysis framework. The use of decision impact evaluation and parameter assessment on decisions might lead to more focused and faster hydrocarbon field (re-)development project execution.
A Core Scale Investigation of Drainage Displacement
Authors: Arab Danial , Kantzas Apostolos , Torsæter Ole , Bryant Steven L. 
Published: June 2020

Abstract
Water flooding has been applied either along with primary production to maintain reservoir pressure or later to displace the oil in conventional and heavy oil reservoirs. Although it is generally accepted that water flooding of light oil reservoirs in oil-wet systems delivers the least oil compared to either water-wet or intermediate-wet systems, there is a lack of systematic research to study water flooding of heavy oils in oil-wet reservoirs. This research gives some new insights on the effect of injection velocity and oil viscosity on water flooding of oil-wet reservoirs.
Seven different oils with a broad range of viscosity ranging from 1 to 15,000 mPa.s at 25 °C were used in fifteen core flooding experiments where injection velocity was varied from 0.7 to 24.3 ft/D (2.5 × 10−6 m/s to 86.0 × 10−6 m/s). Oil-wet sand (with contact angle of 159.31 ± 3.06°) was used in all the flooding experiments. Breakthrough time was precisely determined using an in-line densitometer installed downstream of the core.
Our observations suggest that drainage displacement does not occur unless non-wetting (water) phase pressure exceeds a critical breakthrough capillary pressure. At the same injection velocity, this non-wetting phase invading pressure is a function of the viscosity of the oil being displaced. For the same viscosity ratio, oil recovery monotonically increases with increasing injection velocity suggesting that the flow regime is viscous-dominant for all the viscosities studied. This is consistent with the classical literature on carbonates (deZabala and Kamath, 1995). However, the current work extends the classical learnings to a much wider operational envelope on oil-wet sandstones.
In this paper, it is demonstrated that in an oil-wet system increasing velocity improves forced drainage to the extent that it takes over viscous fingering. For the viscous oil system (15,000 mPa.s), it was found that wettability critically affects the pressure gradient across the core to the extent that one order of magnitude larger pressure gradient was observed in an oil-wet system compared to the completely same system but water-wet. This notable larger pressure gradient in oil-wet system accompanies with delayed water breakthrough leading to incremental (around 30 % OOIP) oil recovery compared to the water-wet case. This is completely opposite to the classical literature on light oils and needs to be further investigated due to the lack of literature on heavy oil domains. Observations reported in this study can provide some useful information about the sizes of the pores being invaded as a function of oil viscosity and wettability, which is a subject of our future microfluidic studies at the pore scale.
Feasibility of Sector Modeling Approach in a Giant Petroleum Field
Authors: Pires Luis , Botechia Vinicius , Schiozer Denis 
Published: June 2020

Abstract
The decision analysis process to develop a petroleum field can be very complex. This process contemplates a set of tasks, which include the study of various representative scenarios, and different production strategies that aid decision-making. However, when it comes to giant reservoirs, the computational requirements of the respective simulation models may be too high. High computational cost may demand simplification that may yield suboptimal solutions so it is desirable to find simplifications that preserve the quality of the solutions. One approach to reduce the simulation requirements is to divide the reservoir into sectors, and to use sector models isolated in the decision making process. This study evaluates the feasibility of using a model of an isolated sector from a giant reservoir in the management of this sector. The observed decrease in the simulation time of the isolated model makes this methodology attractive. However, it is necessary to evaluate in advance the impacts of its use on the flow behavior of this sector when inserted in the Full Field model. The case study presented is a deterministic realization of a reservoir with analogous characteristics to the Mero pre-salt field, with high communication along the reservoir. The global differences found between the isolated model and the Full Field model presented a range that justifies the use of the isolated model in the development process of this sector, without losing significant accuracy in the results. A methodology is proposed to evaluate the differences between both models using field and well indicators. Discussions about the impact of local differences between the two models are presented. The causes of these differences were investigated and attributed to three main factors: the production strategy; changing of boundary conditions; and rock properties of the model.
Impact of Mechanical Entrapment on the Design of Mobility Control in Chemical Enhanced Oil Recovery
Authors: Meulenbroek Bernard , Farajzadeh Rouhi , Bruining Hans 
Published: June 2020

Abstract
The efficiency of polymer enhanced oil recovery largely depends on the propagation of the injected polymer solution, which is mainly influenced by adsorption and mechanical entrapment of polymer. An efficient polymer displacement process is usually designed to maintain a stable front. The impact of mechanical entrapment on the front stability has as yet not been fully investigated. A quantitative evaluation requires accurate solutions of the relevant two-phase flow equations considering adsorption and a history-dependent entrapment function.
The model equations for single phase flow need to solved first and can be used to obtain a few model parameters by comparison to available experimental data. These equations are solved analytically, which yields 1-D concentration and saturation profiles considering both adsorption and entrapment. In addition the pressure history of the displacement process is obtained. The ensuing polymer concentrations with and without entrapment are then considered for the design of the mobility control for a polymer EOR process.
We find that by inclusion of mechanical entrapment, the polymer concentration reduces from the injection point towards the displacement front. The severity of the concentration loss at the front is indicated by the history of the previously entrapped polymer molecules.
Conditions can be chosen to sufficiently reduce the mobility ratio between the polymer and the oil and can show under which conditions the oil can be displaced in a stable manner.
Experimental Investigation of the Extent of the Impact of Halite Precipitation on CO2 Injection in Deep Saline Aquifers
Authors: Edem Donatus , Abba Muhammad , Nourian Amir , Babaie Meisam , Naeem Zainab 
Published: June 2020

Abstract
A laboratory investigation was carried out to experimentally determine the extent of the salt precipitation effects on the petrophysical properties of deep saline aquifer during CO2 storage. This was performed on selected core samples using laboratory core flooding process. The petrophysical properties (Porosity, Permeability) of the core sample were measured before core flooding using Helium Porosimetry and Scanning Electron Microscopy (SEM) to determine the morphology of the core samples. The core samples were saturated with brines of different salinities (5, 15, 25, wt% NaCl) and core flooding process was conducted at a simulated reservoir pressure of 1,000 psig, temperature of 45°C, with varying injection rates of 1.0, 1.5, 2.0, 2.5 and 3.0 ml/min respectively. The obtained results indicated that the porosity and permeability decreased drastically as salinities increases, noticeably because the higher concentration of brine resulted in higher amounts of salt precipitation. Porosity reduction ranged between 0.75% to 6% with increasing brine salinity while permeability impairment ranged from 10% to 70% of the original permeability. The SEM images of the core samples after the flooding showed that salt precipitation not only plugged the pore spaces of the core matrix but also showed significant precipitation around the rock grains thereby showing an aggregation of the salts. This clearly proved that the reduction in the capacity of the rock is associated with salt precipitation in the pore spaces as well as the pore throats. Higher injection rates induced higher salt precipitation which caused reduction in porosity and permeability. This is attributed to the fact that; the higher injection of CO2 vaporizes the formation brine more significantly and thereby increasing brine concentration by removing the water content and enhancing precipitation of salt. These findings provide meaningful understanding and evaluation of the extent of salt precipitation on CO2 injectivity in saline reservoirs. The insight gained could be useful in simulation models to design better injectivity scenarios and mitigation techniques