Research of interaction between expressive and producing wells based on construction of multilevel models

Актуальность исследования обусловлена тем, что гидродинамическая связь между нагнетательной и добывающей скважинами - важнейшее условие полной выработки запасов. Изучение закономерности распределения объемов закачки в пределах целевого объекта - важнейшая задача мониторинга его разработки. На сегодняшний день предприятия нефтегазовой промышленности для этих целей применяют методы гидропрослушивания и индикаторных исследований. Данные методы могут наиболее точно оценить направления движения фильтрационных потоков, но ввиду дороговизны и длительности проведения данных исследований на месторождениях Пермского края проводятся нечасто. В работе предлагается оценивать распределение объемов закачки в пределах элемента системы разработки посредством корреляции накопленных характеристик их работы. Цель: разработка косвенного способа, позволяющего количественно оценить распределение закачиваемой в пласт воды, основанного на использовании промыслового материала. Объект: карбонатные залежи Гагаринского, Озерного и Опалихинского нефтяных месторождений. Методы: геолого-промысловые исследования, корреляционный анализ. Результаты. Многоуровневое статистическое моделирование позволило установить стадийность процесса влияния накопленной закачки на накопленную добычу жидкости и на количественном уровне обосновать граничные значения перехода от одной стадии к другой. Выполненный анализ динамики коэффициента корреляции между накопленными значениями закачки воды и добычи жидкости позволил установить качественные показатели работы системы заводнения в пределах рассматриваемого элемента системы разработки. Полученные качественные показатели работы системы заводнения демонстрируют высокую достоверность практического применения, что подтверждено материалами трассерных исследований, применительно к карбонатным залежам Гагаринского, Озерного и Опалихинского нефтяных месторождений.The relevance of the study is caused by hydrodynamic relation between the injection and production wells is the most important condition for the full development of reserves. Studying the patterns of distribution of injection volumes within its target facility is the most important task of monitoring its development. To date, oil, and gas companies for these purposes use methods of hydraulic monitoring and indicator research. These methods can most accurately assess the direction of movement of the filtration flows, but due to the high cost and duration of these studies they are not often carried out in the Perm Krai fields. The paper proposes to evaluate the distribution of injection volumes within the element of the development system by correlating the accumulated characteristics of their work. The main aim of the study is to develop an indirect method for quantifying the distribution of water injected into the formation based on the use of field materials. Object: carbonate deposits of the Gagarinskoe, Ozernoe and Opalikhinskoe oil fields. Methods: geological and field research, correlation analysis. Results. Multilevel statistical modeling made it possible to establish the stage-by-stage process of the effect of cumulative injection on accumulated fluid production and to substantiate at a quantitative level the boundary values of the transition from one stage to another. The analysis of the dynamics of the correlation coefficient between the accumulated values of water injection and fluid production allowed us to establish qualitative indicators of the waterflooding system within the considered element of the development system. The obtained qualitative indicators of the waterflooding system demonstrate high reliability of practical application, which is confirmed by the materials of tracer studies, as applied to the carbonate deposits of the Gagarinskoe, Ozernoe and Opalikhinskoe oil fields

Analysis of shared common genetic risk between amyotrophic lateral sclerosis and epilepsy

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins

Abstracts of The Second Eurasian RISK-2020 Conference and Symposium

This abstract book contains abstracts of the various research ideas presented at The Second Eurasian RISK-2020 Conference and Symposium.The RISK-2020 Conference and Symposium served as a perfect venue for practitioners, engineers, researchers, scientists, managers and decision-makers from all over the world to exchange ideas and technology about the latest innovation developments dealing with risk minimization

Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies

The epilepsies affect around 65 million people worldwide and have a substantial missing heritability component. We report a genome-wide mega-analysis involving 15,212 individuals with epilepsy and 29,677 controls, which reveals 16 genome-wide significant loci, of which 11 are novel. Using various prioritization criteria, we pinpoint the 21 most likely epilepsy genes at these loci, with the majority in genetic generalized epilepsies. These genes have diverse biological functions, including coding for ion-channel subunits, transcription factors and a vitamin-B6 metabolism enzyme. Converging evidence shows that the common variants associated with epilepsy play a role in epigenetic regulation of gene expression in the brain. The results show an enrichment for monogenic epilepsy genes as well as known targets of antiepileptic drugs. Using SNP-based heritability analyses we disentangle both the unique and overlapping genetic basis to seven different epilepsy subtypes. Together, these findings provide leads for epilepsy therapies based on underlying pathophysiology

Using common genetic variants to find drugs for common epilepsies

Abstract Better drugs are needed for common epilepsies. Drug repurposing offers the potential of significant savings in the time and cost of developing new treatments. In order to select the best candidate drug(s) to repurpose for a disease, it is desirable to predict the relative clinical efficacy that drugs will have against the disease. Common epilepsy can be divided into different types and syndromes. Different antiseizure medications are most effective for different types and syndromes of common epilepsy. For predictions of antiepileptic efficacy to be clinically translatable, it is essential that the predictions are specific to each form of common epilepsy, and reflect the patterns of drug efficacy observed in clinical studies and practice. These requirements are not fulfilled by previously published drug predictions for epilepsy. We developed a novel method for predicting the relative efficacy of drugs against any common epilepsy, by using its Genome-Wide Association Study summary statistics and drugs’ activity data. The methodological advancement in our technique is that the drug predictions for a disease are based upon drugs’ effects on the function and abundance of proteins, and the magnitude and direction of those effects, relative to the importance, degree and direction of the proteins’ dysregulation in the disease. We used this method to predict the relative efficacy of all drugs, licensed for any condition, against each of the major types and syndromes of common epilepsy. Our predictions are concordant with findings from real-world experience and randomized clinical trials. Our method predicts the efficacy of existing antiseizure medications against common epilepsies; in this prediction, our method outperforms the best alternative existing method: area under receiver operating characteristic curve (mean ± standard deviation) 0.83 ± 0.03 and 0.63 ± 0.04, respectively. Importantly, our method predicts which antiseizure medications are amongst the more efficacious in clinical practice, and which antiseizure medications are amongst the less efficacious in clinical practice, for each of the main syndromes of common epilepsy, and it predicts the distinct order of efficacy of individual antiseizure medications in clinical trials of different common epilepsies. We identify promising candidate drugs for each of the major syndromes of common epilepsy. We screen five promising predicted drugs in an animal model: each exerts a significant dose-dependent effect upon seizures. Our predictions are a novel resource for selecting suitable candidate drugs that could potentially be repurposed for each of the major syndromes of common epilepsy. Our method is potentially generalizable to other complex diseases.</jats:p