Análisis de curvas de presión de cabeza en pozos surgentes (Record no. 192874)

MARC details
000 -LEADER
fixed length control field 03368nam a2200313 4500
008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL
Campo de control de longitud fija 260224s2018 xxu esp
041 ## - IDIOMA
Idioma Español
082 ## - CLASIFICACIÓN DEWEY
Número de clasificación 068.82 553.28 C62 2018 0015647
245 00 - TITULO
Título Análisis de curvas de presión de cabeza en pozos surgentes
260 ## - PUBLICACION, DISTRIBUCION, ETC
Lugar de publicación, distribución, etc.
Nombre de publicador, distribuidor, etc.
Fecha de publicación, distribución, etc. 2018
270 ## - FECHA DE CARGA
Fecha de carga 04/07/2022 ; 13/05/2019
300 ## - DESCRIPCION FISICA
Otra extensión 7 p. ; 1-8
520 ## - RESUMEN, ETC
Resumen A well is in natural flow (flowing well) when the pressure at the bottom of it is sufficient to boost its production to the surface. The flowing wells make use of some surface restrictions in order to regulate the flowing rate in such a way that the overall well performance is a function of several variables. Examples of these variables are tubing size, choke size, wellhead pressure, flow line size, and perforation density. This implies that changing any of these variables will alter well performance.One of the techniques for the analysis of the production is studying the wellhead pressure declination, since, in critical flow conditions, flow is a function of wellhead pressure. From wellhead pressure visualization you can identify the behavior of each well and determine the presence of paraffin or other materials affecting its production or, in the worst case, cause suspension of extraction process.The present work performs the analysis of wellhead pressure curves using data science, with the purpose predict pressure curves and the early identification of anomalies that could occur for timely correction.The data in this work correspond to 130 flowing wells from NOC Oil Sur. The study began with a filtering process of the pressure curve, with two specific objectives: first, eliminate atypical values from the time series, and second, smooth the curve in such a way that future predictions can be performed.Next, the ARIMA methodology (Auto-regressive integrated moving average) was applied with the purpose of predicting values of the curve. This is based on the past values of the time series to infer the future values, the trend characteristic of the curve was used to apply this methodology.Then, to identify the anomaly a model was designed based on the declination of the curve. The pressure declination curve is a descending exponential, so the first and second derivatives indicate the trend (ascending - descending) and curvature (concave or convex) of it. Once these values are available, they are classified according to the anomaly: paraffin, encrustation or obstruction.Finally, the model is being tested in the control room in Loma Campana, delivering a probability of occurrence of any of the anomalies named every hour.
773 ## - CORRECCIÓN
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942 ## - DESC. DE MATERIAL
Tipo de item KOHA Congresos (trabajos presentados)
100 1# - RESPONSABLE PERSONAL
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111 2# - AUTORIDAD DE CONGRESO
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9 (RLIN) 573
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650 #0 - MATERIA
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Término tópico Pozos
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9 (RLIN) 58927
856 ## - LINK
Link <a href="https://biblioteca.iapg.org.ar/ArchivosAdjuntos/Conexplor2018/SGeot/1691.pdf">https://biblioteca.iapg.org.ar/ArchivosAdjuntos/Conexplor2018/SGeot/1691.pdf</a>
Holdings
Biblioteca propietaria Biblioteca actual Ubicación Fecha de adquisición Inventario Total de préstamos Signatura topográfica Inventario Fecha de carga Tipo de item KOHA
IAPG-Colección IAPG-Colección 068.82 553.28 C62 2018 0015647 06/03/2026 200065182   068.82 553.28 C62 2018 0015647 200065182 06/03/2026 Congresos (trabajos presentados)


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