ESTUDIO DE LA TÉCNICA TOE TO HEEL STEAMFLOOD, THSF: UNA NUEVA OPCIÓN PARA EL RECOBRO DE CRUDO PESADO

RESUMEN El proceso Toe to Heel Steam Flood (THSF, por la sigla en inglés) es una novedosa técnica de recuperación mejorada de crudo pesado. Esta hace parte de las tecnologías Toe to Heel, las cuales aprovechan las grandes áreas de drenaje de los pozos horizontales. El THSF utiliza un par de pozos para la explotación del petróleo, uno vertical para inyectar vapor de manera continua y uno horizontal, que permite la producción de crudo junto con agua caliente resultante de la condensación del vapor inyectado. Debido a las características de la configuración de pozos, el factor de recobro obtenido tras la aplicación del proceso es significativamente alto. Además, se obtiene una respuesta casi inmediata en el incremento de la producción de petróleo usando una baja relación entre el vapor requerido y el crudo producido.En el presente trabajo se analizan los principales aspectos teóricos del THSF, como alternativa para la recuperación de crudo pesado y extrapesado. También, son analizados los resultados de un estudio de simulación numérica, el cual se desarrolló con el fin de visualizar la eficiencia del proceso y compararlo con algunas técnicas convencionales de inyección de vapor. Palabras claves: Recobro Mejorado de Petróleo, THSF, simulación de yacimientos, técnicas de corta distancia. ABSTRACT The process Toe to Heel Steam Flood (THSF, for short) is a novel technique for enhanced heavy oil recovery. It is part of the Toe to Heel technologies, which exploit the large drainage areas of the horizontal wells. The configuration of THSF uses a pair of wells, a vertical on enject steam in continuous form and a horizontal, which allows the production of crude with hot water from the condensation steam injected. Due to the characteristics of the configuration of wells used, the recovery factor obtained after to put into practice the process is significantly higher. Besides, it gets an almost immediate increase in oil production and it shows a low ratio between the required steam and crude produced.In this paper are analyzed the main theoretical aspects of THSF as an alternative for the heavy and extra-heavy oil recovery. Also are discussed the results of a numerical simulation study, which was developed in order to display the efficiency of the process and to compare with some conventional techniques of steam injection. Keywords: Enhanced Oil Recovery (EOR), THSF, reservoir simulation, short distance techniques

Modelos Proxy, alternativa para reducir los tiempos de cómputo durante la simulación numérica

La simulación numérica de yacimientos es una herramienta que ha venido evolucionando de la mano de la industria petrolera, su objetivo fundamental es predecir el comportamiento de un yacimiento dado y posteriormente encontrar el escenario óptimo para aumentar la recuperación de hidrocarburos. Sin embargo, los estudios de simulación numérica pueden llegar a ser muy costosos por factores como: tamaño de la grilla y la robustez del estudio a realizar (asociado a mayores tiempos de cómputo y de análisis de resultados); además del tiempo que implicaría llegar a evaluar los múltiples escenarios posibles para definir la mejor estrategia de explotación. Es por esta razón, que los ingenieros de yacimientos se apoyan en herramientas estadísticas para aplicar los estudios de simulación numérica orientados al ajuste histórico, análisis de sensibilidad, análisis de incertidumbre, predicción y estrategias de optimización de producción. Dentro de estas herramientas estadísticas se encuentran los Modelos Proxy, los cuales surgen como alternativa para reducir los tiempos de cómputo en estudios de imulación numérica que no requieran un alto grado de exactitud en sus resultados. Este artículo busca contextualizar al lector sobre el significado de los modelos proxy y su utilidad durante los estudios de simulación numérica de yacimientos, además de presentar un ejemplo de aplicación.The reservoir simulation is a tool which had been evolving at the same time than the petroleum industry; its main purpose is to predict the behavior of a reservoir and afterward finding the optimum scenario in order to increase the oil recovery. However, numerical simulation studies could be very expensive because factors such as grid size and detail of the study to develop (It is associated to long computational and analysis times). Furthermore the time it would take to evaluate multiple possible scenarios to define the best exploration strategy. For this reason, field engineers use statistical tools during numerical simulation studies oriented to history match, sensitivity analysis, uncertainty analysis, optimization and forecasting. One of these statistical tools is the Proxy model, it appears as an alternative to reduce computational times which does not need a high accuracy grade in the results. This article looks for a reader contextualization about the meaning of Proxy model and its value during reservoir simulation studies, and also to present an application study

Ajuste de una prueba de tubo de combustion usando un modelo simplificado de reacciones

La implementación de un proceso de inyección de aire en un yacimiento de crudo pesado se fundamenta en un buen diseño experimental. Una de las principales pruebas de este diseño es la prueba de tubo de combustión, de la cual se obtienen las bases de diseño para implementar el proceso a escala piloto. Sin embargo, es de gran importancia realizar un ajuste numérico de la prueba de tubo de combustión para crear un modelo numérico a escala piloto. Usando el modelo anterior se puede evaluar el desempeño del proceso antes de su implementación directa a un piloto de campo.Teniendo en cuenta lo anterior, en el presente estudio se construyó un modelo numérico en 1D mediante el ajuste de una prueba de tubo de combustión realizada a un crudo colombiano. Para realizar este ajuste se usaron dos reacciones con el objetivo de simular los efectos térmicos del proceso. La primera de estas reacciones tiene como único objetivo depositar el coque, el cual servirá de combustible para la segunda reacción denominada de combustión. Como resultado de la implementación del modelo anterior fue posible ajustar los picos de temperatura, el coque depositado y la velocidad del frente, variando los parámetros cinéticos de las dos reacciones.Palabras clave: combustión in-situ, prueba tubo de combustión, modelo de simulación, velocidad frente de combustión

EVALUACIÓN DEL AJUSTE DE PRUEBAS DE TUBO DE COMBUSTIÓN UTILIZANDO SIMULACIÓN NUMÉRICA

RESUMENCombustión in situ es un método de recobro mejorado con un alto potencial para desarrollarse como técnica de recuperación en campos de crudo pesado a nivel mundial. A diferencia de otros procesos como la inyección de vapor, donde la energía es generada en superfcie, en un proceso de combustión in situ ésta es generada y entregada directamente en el yacimiento. Por otra parte, este método involucra mecanismos muy complejos, que difcultan su representación adecuada a través de modelos físicos. Una prueba de laboratorio muy útil para realizar una evaluación técnica de un proceso de combustión es la prueba de tubo, ésta entrega información sobre las características de quemado de un crudo en especial y permite establecer a partir de la composición de los fuidos producidos algunos parámetros necesarios para diseñar un proceso de combustión in situ. Sin embargo, los resultados obtenidos en las pruebas de tubo no son directamente aplicables a campo, debido a que como se mencionó antes, en combustión intervienen muchos fenómenos que difcultan el escalamiento a campo. Por tanto, fue necesario estudiar el efecto de diferentes parámetros operacionales y de yacimiento, que conllevaron a obtener resultados distintos.Palabras Clave: pruebas de tubo, parámetros de ajuste, modelo de simulación, escalas de simulación. ABSTRACTCombustion in situ is an enhanced oil recovery method with a high potential to develop as a recovery technique in heavy oil felds worldwide. Unlike other processes like steam injection where the energy is sent from the surface, the energy for in situ combustion process is generated and delivered directly into the reservoir. Moreover, this method involves very complex mechanisms that impede the adequate representation through physical models. A very useful laboratory test to perform a technical review of combustion process is tube tests, it provide information about the characteristics of burning of a particularly crude and allow setting from the composition of produced fuids, some necessary parameters to design an in situ combustion process. However, the results of the test tube are not directly applicable to feld, because as mentioned earlier, combustion involves many diffcult scaling phenomena in the feld. It was therefore necessary to study the effect of different operational and reservoir parameters, which led to different results.Keywords: Combustion tube tests, setting parameters, simulation models, simulation scales

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost