bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ocena przydatności wykorzystania geometrycznych parametrów przestrzeni porowej z obrazów tomograficznych w kontekście pomiarów NMR, porozymetrii rtęciowej i porozymetrii helowej
Authors:   Instytut Nafty i Gazu – Państwowy Instytut Badawczy, Drabik Katarzyna , Krakowska-Madejska Paulina ,   AGH Akademia Górniczo-Hutnicza im. St. Staszica w Krakowie, Puskarczyk Edyta ,   AGH Akademia Górniczo-Hutnicza im. St. Staszica, Wydział Wiertnictwa, Nafty i Gazu, Dohnalik Marek ,   Instytut Nafty i Gazu - Państwowy Instytut Badawczy
Published: November 2021

Głównym celem pracy była ocena przydatności wyników interpretacji ilościowej, uzyskanej z obrazowania wewnętrz­nej struktury próbek skał z wykorzystaniem metody tomografii komputerowej, do szacowania parametrów zbiornikowych takich jak porowatość czy przepuszczalność. W pracy badano zależności korelacyjne pomiędzy parametrami przestrzeni porowej uzyskanymi z analizy obrazów tomografii komputerowej a wynikami standardowych badań laboratoryjnych. Materiał badawczy składał się z próbek piaskowców czerwonego spągowca, facji eolicznej, pobranych z obszaru Niżu Polskiego. Do analiz wybrano kilkadziesiąt próbek skał piaskowców czerwonego spągowca, dla których policzono 69 parametrów. Interpretacja jakościowa i ilościowa polegała na porównaniu parametrów otrzymanych z analizy obrazu tomograficznego z wcześniej uzyskanymi wynikami analiz laboratoryjnych obejmujących następujące metody badawcze: porozymetrię helową (Por.He), spektrometrię jądrowego rezonansu magnetycznego (NMR), porozymetrię rtęciową (Por.Hg) i przepuszczalność absolutną (przepuszcz). Utworzono macierze korelacji dla wszystkich dostępnych parametrów, do pracy wybrano korelacje istotne, o najwyższym współczynniku korelacji liniowej. Zaobserwowano istotne zależności liniowe pomiędzy parametrami wyznaczonymi z analizy obrazów CT i innych metod badawczych. Uzyskano modele pozwalające na szacowanie przepuszczalności, porowatości i zawartości wody nieredukowalnej na podstawie parametrów geometrycznych otrzymanych z obrazów tomograficznych (współczynnik kształtu, charakterystyka Eulera czy powierzchnia właściwa). W efekcie możliwe jest wstępne oszacowanie parametrów petrofizycznych jedynie na bazie wyników z nieniszczącej metody CT. W przypadku obrazowania tomograficznego pełnych rdzeni uzyskane związki pozwalają na wstępną estymację rozkładu porowatości i gęstości objętościowej w całym rdzeniu, co może być pomocne podczas typowania miejsc do poboru próbek rdzeni przeznaczonych do szczegółowych badań laboratoryjnych.
Asian Hornet, Vespa velutina Lepeletier 1836 (Hym.: Vespidae), Venom Obtention Based on an Electric Stimulation Protocol
Authors: Feás Xesús , Vidal Carmen , Vázquez-Tato M. Pilar , Seijas Julio A. 
Published: November 2021

The yellow-legged Asian hornet (Vespa velutina Lepeletier 1836 (Hymenoptera: Vespidae)) is naturally distributed in China, Southeast Asia and India; however it has since detected outside of its native area, confirmed as being established in South Korea, Europe and Japan. Health risks and deaths caused by the invasive Vespa velutina stings have become a public health concern, being the most common cause of anaphylaxis due to hymenopterans in some European regions. This in turn has led to increased demand from medical practitioners and researchers for Vespa velutina venom for diagnostic and therapeutic purposes. In this study, a straightforward, quick and inexpensive method for obtaining Vespa velutina venom by electric stimulation is described. The venom extracts were analyzed by nuclear magnetic resonance spectroscopy (1H-NMR), confirming the composition of the obtained material. The availability of Vespa velutina venom will lead to improved diagnostic and therapeutic methods, mainly by venom immunotherapy (VIT), in patients allergic to this invasive species.
Joint Optimization of Well Completions and Controls for CO2 Enhanced Oil Recovery and Storage
Authors: Chen Bailian , Pawar Rajesh 
Published: November 2021

Summary
Carbon dioxide (CO2) enhanced oil recovery (EOR) is considered one of the technologies to help promote larger scale deployment of geologic CO2 storage because of associated economic benefits through CO2 storage, associated benefits of oil recovery, and the 45Q tax credit (a tax incentive that would reduce CO2 emission in the United States) as well as potential for utilization of existing infrastructure. The objective of this study is to demonstrate how optimal operation strategies (including well completions and controls) can be used to optimize both CO2 storage and oil recovery. The optimization problem was focused on joint estimation of well completions (i.e., fraction of injection/production well perforations in each reservoir layer) and CO2 injection/oil production controls [i.e., rates or bottomhole pressures (BHPs)] that maximize the net present value (NPV) in a combined CO2-EOR and CO2 storage operation. We used the newly developed stochastic simplex approximate gradient (StoSAG), one of the most efficient optimization algorithms in the reservoir optimization community, to solve the optimization problem. The performance of the joint optimization approach was compared with the performance of the well-control-only optimization approach. The superiority of joint optimization was demonstrated with two examples. In addition, the performance of co-optimization of CO2 storage and oil recovery approach was compared with the performances of maximization of only CO2 storage and maximization of only oil recovery approaches.
Strategies to Enhance the Performance of Gaussian Mixture Model Fitting for Uncertainty Quantification
Authors: Gao Guohua , Vink Jeroen , Saaf Fredrik , Wells Terence 
Published: November 2021

Summary
When formulating history matching within the Bayesian framework, we may quantify the uncertainty of model parameters and production forecasts using conditional realizations sampled from the posterior probability density function (PDF). It is quite challenging to sample such a posterior PDF. Some methods [e.g., Markov chain Monte Carlo (MCMC)] are very expensive, whereas other methods are cheaper but may generate biased samples. In this paper, we propose an unconstrained Gaussian mixture model (GMM) fitting method to approximate the posterior PDF and investigate new strategies to further enhance its performance.
To reduce the central processing unit (CPU) time of handling bound constraints, we reformulate the GMM fitting formulation such that an unconstrained optimization algorithm can be applied to find the optimal solution of unknown GMM parameters. To obtain a sufficiently accurate GMM approximation with the lowest number of Gaussian components, we generate random initial guesses, remove components with very small or very large mixture weights after each GMM fitting iteration, and prevent their reappearance using a dedicated filter. To prevent overfitting, we add a new Gaussian component only if the quality of the GMM approximation on a (large) set of blind-test data sufficiently improves.
The unconstrained GMM fitting method with the new strategies proposed in this paper is validated using nonlinear toy problems and then applied to a synthetic history-matching example. It can construct a GMM approximation of the posterior PDF that is comparable to the MCMC method, and it is significantly more efficient than the constrained GMM fitting formulation (e.g., reducing the CPU time by a factor of 800 to 7,300 for problems we tested), which makes it quite attractive for large-scale history-matching problems.
NOTE: This paper is also published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.
Integrated Production Model as a Tool for Optimization the Development Strategy of the Sakhalin Oil and Gas Condensate Field
Authors: Doroshenko Oleksandr , Cimic Miljenko , Singh Nicholas , Machuzhak Yevhen 
Published: November 2021

Abstract
A fully integrated production model (IPM) has been implemented in the Sakhalin field to optimize hydrocarbons production and carried out effective field development.
To achieve our goal in optimizing production, a strategy has been accurately executed to align the surface facilities upgrade with the production forecast.
The main challenges to achieving the goal, that we have faced were:
All facilities were designed for early production stage in late 1980's, and as the asset outdated the pipeline sizes, routing and compression strategies needs review. Detecting, predicting and reducing liquid loading is required so that the operator can proactively control the hydrocarbon production process. No integrated asset model exists to date.
The most significant engineering tasks were solved by creating models of reservoirs, wells and surface network facility, and after history matching and connecting all the elements of the model into a single environment, it has been used for the different production forecast scenarios, taking into account the impact of infrastructure bottlenecks on production of each well.
This paper describes in detail methodology applied to calculate optimal well control, wellhead pressure, pressure at the inlet of the booster compressor, as well as for improving surface flowlines capacity.
Using the model, we determined the compressor capacity required for the next more than ten years and assessed the impact of pipeline upgrades on oil gas and condensate production.
Using optimization algorithms, a realistic scenario was set and used as a basis for maximizing hydrocarbon production.
Integrated production model (IPM) and production optimization provided to us several development scenarios to achieve target production at the lowest cost by eliminating infrastructure constraints.
Predicting of the Geometrical Behavior of Formations in Subsurface Based on the Analysis of LWD/MWD Data While Drilling Horizontal Wells
Authors: Tyvonchuk Serhii Petrovych 
Published: November 2021

Abstract
The successful penetration of oil and gas formations by a horizontal well depends on the accuracy of the forecast of the depth and angle of the layers’ dip at the entry point. Methods and mathematical algorithms for predicting the geometric behavior of formations during drilling of a horizontal well at the stage of its approach to the entry point into target productive horizons are developed.
The relationship between the formation dip, their stratigraphic thickness, and apparent vertical thickness in vertical and sub-horizontal wells is considered. It is shown that even small angles of inclination can lead to a significant influence on the prediction of the point of formation opening by a horizontal well. A detailed correlation of the offset well section with a horizontal well one while drilling was used for the analysis. A method for predicting the depth of disclose of the target formation by a horizontal well based on the change in the apparent vertical thickness is shown. A mathematical algorithm for calculating the apparent bedding angle on the basis of initial and while drilling data has been obtained. The calculated bedding angle allows predicting the depth of the target formation penetration with a horizontal well.
The proposed method for predicting the horizontal well landing point depth allows avoiding errors associated with non-horizontal layering. The use of the proposed technique when drilling a number of horizontal wells in the oil fields of the Dnieper-Donets Basin (DDB) and the Pre-Carpathian Foredeep made it possible to determine with high accuracy the apparent bedding angle, even at their small values. The calculations made it possible to predict the depth of entry into the target formation during drilling with high accuracy. This is especially important in the context of small oil deposits, where it is impossible to make significant adjustments to the lateral position of the horizontal part of the wellbore. The predicted depths of the entry points into the formations were confirmed by the drilling results.
The use of the proposed method makes it possible to perform high-quality geosteering while drilling horizontal wells at the stage of approaching the target formation entry point using the minimum data set.
The simplicity of the method allows you to quickly analyze the geological section penetrated by a horizontal well and determine its geometric behavior. This approach makes it possible to successfully open pay formations with horizontal wells even without using a pilot well.
A Case Study of High-Rate Multistage Hydraulic Fracturing in Petrikov Horizon of the Pripyat Trough
Authors: Mironenko Kirill Victorovich , Voytekhin Oleg Leonidovich , Marchenko Vladimir Vladimirovich 
Published: November 2021

Abstract
Currently, the vast majority of the oil fields of the Republic of Belarus are at the final stage of development. In this connection, in order to expand the resource base, Belarusian oil companies are assigned with the task of searching, exploring and developing hard-to-recover reserves. In recent years, a number of geological works have been carried out to search and study the sedimentary cover rocks of the Belarusian part of the Pripyat Trough, the results of these works were the discovery of promising deposits of the Petrikov Horizon of the Upper Devonian.
These deposits are represented by dense fractured carbonate rocks with ultra-low permeability (less than 0.01 mD) and low effective porosity (up to 10%). The most promising technology for the development of such reservoirs is the drilling of horizontal wells and the subsequent implementation of Multistage hydraulic fracturing.
This article presents the experience of developing ultra-low-permeability reservoirs in the Republic of Belarus in the period 2014-2021, briefly describes the main technologies used, the evolution of technological solutions for effective involvement in the active development of hard-to-recover reserves.
The SMART SRP Well – Application of Edge Analytics for Automated Well Performance Control and Condition Monitoring in a Mature Brownfield Environment – A Case Study from Austria
Authors: Windisch Christian 
Published: November 2021

Abstract
This paper presents a holistic approach to modern oilfield and well surveillance through the inclusion of state-of-the-art edge computing applications in combination with a novel type of data transmission technology and algorithms developed in-house for automatic condition monitoring of SRP systems. The objective is to enable the responsible specialist staff to focus on the most important decisions regarding oilfield management, rather than wasting time with data collection and preparation.
An own operated data communication system, based on LPWAN-technology transfers the dyno-cards, generated by an electric load cell, into the in-house developed production assistance software platform. Suitable programmed AI-algorithms enable automatic condition detection of the incoming dyno cards, including conversion and analysis of the corresponding subsurface dynamograms. A smart alarming system informs about occurring failure conditions and specifies whether an incident of rod rupture, pump-off condition, gas lock or paraffin precipitation occurred in the well. A surface mounted measuring device delivers liquid level and bottomhole pressure information automatically into the software. Based on these diverse data, the operations team plans the subsequent activities.
The holistic application approach is illustrated using the case study of an SPR-operated well in an Austrian brownfield.
Influence of Abandonment Pressure on Recoverable Reserves, Special Application to the Depleted Dnipro-Donetsk Basin Reservoirs
Authors: Cimic Miljenko , Sadivnyk Michael , Doroshenko Oleksandr , Kovalchuk Stepan 
Published: November 2021

Abstract
Volumetric gas reservoirs are driven by the compressibility of gas and a formation rock, and the ultimate recovery factor is independent of the production rate but depends on the reservoir pressure. The gas saturation in the volumetric reservoir is constant, and the gas volume is reduced causing pressure drop in the reservoir. Due to this reason, it is crucial to minimize the abandonment pressure to the lowest possible level. Concerning Dnipro-Donetsk Basin (DDB) gas reservoirs, it is widespread to recover sometimes more than 90% of the OGIP. Often, OGIP was estimated not considering lower permeability gas layers due to inaccurate logging equipment used in the past, causing that such layers were not included in the total netpay. This is one of the reasons for OGIP overestimation and higher recovery factors. On many P/Z graphs, we observe that at certain drawdown, lower permeability reservoirs kick in lifting up P/Z plot curve.
Abandonment pressure is a major factor in determining recovery efficiency. Permeability and skin are usually the most critical factors in determining the magnitude of the abandonment pressure. Reservoirs with low permeability will have higher abandonment pressures than reservoirs with high permeability. A specific minimum flow rate must be sustained to keep the well unloading process, and a higher permeability will permit this minimum flow rate at lower reservoir pressure.
Abandonment pressure will depend on wellhead pressure, friction and hydrostatic pressures in the system, pressure drop in reservoir, and pressure drop due to skin. This last factor is often neglected, which sometimes leads to a significant reduction of the recovery factor. It is common practice that skin factor and pressure drop due to the skin are solved with well stimulation. Also, well stimulation has its limits concerning the level of reservoir pressure. It is very common that the stimulation effect of low reservoir pressure well is negligible or even negative. This is caused by the minimum required drawdown to flow back a stimulating aqueous fluid out of the reservoir. The required minimum drawdown is caused by the Phase Trapping Coefficient (PTC), which drives reservoir stimulation fluid cleaning behavior.
For water drive gas reservoirs, Cole (1969) suggests that the recovery is substantially less than recovery from bounded gas reservoirs. As a rule of thumb, recovery from a water-drive reservoir will be approximately 50 to 75% of the initial gas in place. The structural location of producing wells and the degree of water coning are essential considerations in determining ultimate recovery. In the cases studied in this paper, we consider gas and rock expansion reservoir energy, if abandonment pressure needs to be coupled with a water drive, then it is recommended to use a numerical, not analytical approach.
Adoption of Integrated Asset Modeling Approach to Kick-Start the Corporate Digital Transformation Strategy
Authors: Siew Hiang Khor , Volodymyr Petrunyak , Melnyk Yevgen A. , Oleksii Prykhodchenko , Viktor Stefaniv , Andrew Dogar , Michael Ojukwu , Andres Viscaino 
Published: November 2021

Abstract
The adoption of an integrated asset modeling approach was explored to kick-start the corporate digital transformation strategy for its oil and gas section. Besides the integrated asset model, the digital initiatives included predictive maintenance, well performance optimization, and a flow assurance advisor aimed at daily production operations and maintenance, creating a pathway to the digital oilfield (DOF). The integrated asset model would be the main pillar of DOF realization and implementation, its offered technology aimed at short-term, medium-term, and long-term planning.
The adopted well-proven integrated asset modeling methodology enabled a geological complex with a high-fidelity physics reservoir model, multiple interdependent wells, pipeline networks, process facility models to be integrated seamlessly on a single platform for validation of its existing production operation strategy and field development plan. The black-oil reservoir model was history matched, and the production network models had detailed wellbore and pipeline hydraulics calibrated with the latest well-test data. The compositional fluid modeling allowed the capture of any flow assurance issues that arose across the networks, which were mapped to the corresponding process facility models with physical specifications and operational constraints defined.
A fully integrated asset model was developed for the studied asset, where liquid/vapor tables were prepared for black-oil delumping (Ghorayeb and Holmes, 2005) of the reservoir models to surface network models (Mora et al. 2015), while fluid models of both production network and process models were validated before mapping to ensure fluid fidelity. The availability of this integrated asset model with an embedded spreadsheet program incorporating some simple economic calculations allowed the flexibility of short-term production optimization and long-term asset planning, which was focused to provide all the vital valuable inputs to better field management, fast and accurate decision making, and optimum safe operation of process units in meeting the sales contract.
The integrated asset model offered a platform for engineers from different domains to collaborate with aligned common operational and planning objectives. It empowered assessments of production operation strategy and field development scenarios conducted at full field level from pore to process. The customized reporting, the ability to connect to other tools, and to push results to dashboards helped to kick-start the corporate digital transformation strategy.