Oil and Gas flow Anomaly Detection on offshore naturally flowing wells using Deep Neural Networks

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceThe Oil and Gas industry, as never before, faces multiple challenges. It is being impugned for being dirty, a pollutant, and hence the more demand for green alternatives. Nevertheless, the world still has to rely heavily on hydrocarbons, since it is the most traditional and stable source of energy, as opposed to extensively promoted hydro, solar or wind power. Major operators are challenged to produce the oil more efficiently, to counteract the newly arising energy sources, with less of a climate footprint, more scrutinized expenditure, thus facing high skepticism regarding its future. It has to become greener, and hence to act in a manner not required previously. While most of the tools used by the Hydrocarbon E&P industry is expensive and has been used for many years, it is paramount for the industry’s survival and prosperity to apply predictive maintenance technologies, that would foresee potential failures, making production safer, lowering downtime, increasing productivity and diminishing maintenance costs. Many efforts were applied in order to define the most accurate and effective predictive methods, however data scarcity affects the speed and capacity for further experimentations. Whilst it would be highly beneficial for the industry to invest in Artificial Intelligence, this research aims at exploring, in depth, the subject of Anomaly Detection, using the open public data from Petrobras, that was developed by experts. For this research the Deep Learning Neural Networks, such as Recurrent Neural Networks with LSTM and GRU backbones, were implemented for multi-class classification of undesirable events on naturally flowing wells. Further, several hyperparameter optimization tools were explored, mainly focusing on Genetic Algorithms as being the most advanced methods for such kind of tasks. The research concluded with the best performing algorithm with 2 stacked GRU and the following vector of hyperparameters weights: [1, 47, 40, 14], which stand for timestep 1, number of hidden units 47, number of epochs 40 and batch size 14, producing F1 equal to 0.97%. As the world faces many issues, one of which is the detrimental effect of heavy industries to the environment and as result adverse global climate change, this project is an attempt to contribute to the field of applying Artificial Intelligence in the Oil and Gas industry, with the intention to make it more efficient, transparent and sustainable

Current-based Techniques for Condition Monitoring of Pumps

[ES] Las bombas hidráulicas son el núcleo de muchos procesos en la industria y el sector servicios. Conviene tener en cuenta que los motores eléctricos son responsables del 69% del consumo de energía eléctrica en la industria, siendo en torno a un 22% de motores utilizados para el accionamiento de bombas. Los fallos de estas bombas pueden provocar averías en el proceso y, por lo tanto, implican altos costes económicos para el operador de la planta. Además, un funcionamiento defectuoso de las bombas conlleva una reducción de la eficiencia energética de la planta. De forma habitual, se utilizan principalmente dos tipos de estrategias orientadas al mantenimiento de maquinaria. Una estrategia de mantenimiento (mantenimiento preventivo) consiste en la sustitución de las piezas desgastadas en un intervalo de tiempo fijo. Este tipo de estrategia presenta muchas desventajas asociadas a la escasa optimización en el uso de los recursos y al consiguiente impacto económico. Por otro lado, la estrategia basada en la condición del equipo (mantenimiento basado en la condición) liga el reemplazo de las piezas desgastadas al estado del equipo, el cual es monitorizado a través de señales adquiridas mediante sensores. Sin embargo, el uso de sensores tiene algunos inconvenientes, como costes de inversión adicionales, posibles problemas en el montaje del sensor y posibles fallos del mismo. El análisis de la señal de corriente no se ha utilizado de forma habitual en la práctica para evaluar el estado de la bomba, aunque en muchas aplicaciones se dispone de sensores de corriente ya instalados que se podrían utilizar a tal fin. Se ha demostrado que técnicas basadas en el análisis de la corriente resultan de gran utilidad para diagnosticar varios tipos de fallos en motores eléctricos. De hecho, el análisis de la firma de corriente del motor se utiliza hoy en día ampliamente en la industria, especialmente para el diagnóstico de fallos en motores de inducción. En la presente tesis, se evalúa la utilización de la técnica de análisis de corrientes para el diagnóstico de fallos típicos relacionados con las bombas en diferentes aplicaciones. Se investigan tres tipos de bombas diferentes: bombas en línea de rotor húmedo, bombas de rotor seco y bombas sumergibles. En la tesis se han adaptado diversas técnicas, previamente empleadas para la detección de fallos en motores, al diagnóstico de fallos en la propia bomba. Los resultados indican que fallos como obstrucción de la bomba, fisura del impulsor y desgaste de los cojinetes influyen especialmente en dos frecuencias del espectro de corriente, las cuales pueden utilizarse como base de estrategias de mantenimiento basadas en la condición. En concreto, en las bombas de rotor húmedo, estos dos indicadores de fallo varían sensiblemente en función del punto de carga hidráulica de la bomba. Con la ayuda de un método de extracción de características basado en la motor reference frame theory, se demuestra que las mencionadas frecuencias pueden analizarse en tiempo real en un entorno industrial. Además, se presentan directrices para la monitorización en la nube y se valida con la ayuda de ensayos de laboratorio. Adicionalmente, se demuestra que los fallos son también detectables al analizar la corriente de arranque mediante herramientas de descomposición tiempo-frecuencia. Este hito no se había abordado anteriormente en la literatura técnica del área en lo referente a la detección de fallos en bombas. En conclusión, los resultados de este trabajo demuestran que los métodos de diagnóstico basados en la corriente pueden detectar con éxito diversos tipos de fallo en bombas, lo cual constituye un punto de gran interés para las industrias que utilicen estos activos en sus procesos.[CA] Les bombes hidràuliques són el nucli de molts processos en la indústria i en el sector dels serveis. Cal mencionar que els motors elèctrics són responsables del 69% del consum de la energia elèctrica en la indústria, sent al voltant del 22% dels motors utilitzats per l'accionament de bombes. Les fallades d'aquestes bombes poden causar avaries en els processos, i per tant, representen un alt cost econòmic per a l'operador de la planta. A més a més, un funcionament defectuós en les bombes representa una reducció de l'eficiència energètica de la planta. De manera habitual, s'utilitzen principalment dos tipus d'estratègies orientades al manteniment de la maquinària. Una estratègia de manteniment (manteniment preventiu) consisteix en la canvi de les peces desgastades en un interval fixe de temps. Aquest tipus d'estratègia presenta molts desavantatges associats a la reduïda optimització en el ús dels recursos i el seu impacte econòmic. D'altra banda, la estratègia basada en la condició dels equipaments (manteniment basat en la condició) enllaça la substitució de les peces desgastades al estat de l'equip, el qual es monitoritzat per mig de senyals adquirides per sensors. No obstant això, el ús de sensors té alguns inconvenients com costos d'inversió addicionals, possibles problemes al muntatge i possibles fallades. L'anàlisi dels senyals de corrent no s'utilitzen de manera habitual en la pràctica per avaluar l'estat de la bomba, encara que en moltes aplicacions, estos sensors es troben instal·lats i es podrien fer servir per a aquesta finalitat. Ha estat demostrat que les tècniques basades en l'anàlisi de la corrent són de gran utilitat per el diagnosi de diversos tipus de fallades en motors elèctrics. De fet, l'anàlisi de la firma de la corrent del motor s'utilitza àmpliament en l'indústria, especialment per el diagnosi de fallades en motors d'inducció. En la present tesi, s'avalua l'utilització de la tècnica d'anàlisi de corrents per el diagnosi de fallades típiques relacionades en bombes per a diferents aplicacions. Se investiguen tres tipus de bombes diferents: bombes en línia de rotor humit, bombes de rotor sec i bombes submergibles. En aquesta tesi se han adaptat diverses tècniques, prèviament utilitzades en el diagnosi de màquines elèctriques, per al diagnosi de la pròpia bomba. Els resultat indiquen que les fallades com obstrucció de la bomba, la fissura de l'impulsor i el desgast dels coixinets influeixen especialment en dos freqüències de l'espectre de la corrent, les quals es poden utilitzar com a base per a una estratègia de manteniment basada en la condició. Particularment, en les bombes de rotor humit, aquestos dos indicadors de fallada varíen sensiblement en funció del punt de càrrega hidràulica de la bomba. En l'ajuda de un mètode d'extracció de característiques basat en la "motor reference frame theory", es demostra que les mencionades freqüències es poden analitzar en temps real en un entorn industrial. A més a més, es presenten directrius per la monitorització en el núvol i es valida en l'ajuda de assajos en el laboratori. Addicionalment, es demostra que les fallades són també detectables quan s'analitza la corrent d'arrancada mitjançant ferramentes de descomposició temps-freqüència. Aquest fet no ha estat analitzat prèviament en cap tipus de literatura tècnica dins del camp de detecció de fallades en bombes. En conclusió, els resultats d'aquest treball demostren que els mètodes de diagnosi basats en la corrent poden detectar en èxit diversos tipus de fallades en bombes, el qual constitueix un punt d'interés per a l'indústria que utilitzen aquest tipus de actiu en els seus processos.[EN] Pumps are the heart of many processes in industry and service sector. Electric motors are responsible for 69% of electric energy consumption in industry, with 22% of them being used for the operation of pumps. Pump faults can lead to process breakdowns and are thus related to high costs for the plant operator. Furthermore, faulty operation of pumps reduces the energy efficiency of the plant. In many cases, a time-based maintenance strategy is applied, which means that typical wear parts are replaced within defined time cycles, which comes with some drawbacks such as poor resource efficiency and high costs. Condition-based maintenance strategies - meaning that the replacement of parts is planned based on the condition of the pump - are often based on the evaluation of sensor signals like vibration or noise. However, the use of sensors also has some drawbacks, such as additional investment costs, frequent problems with the sensor mounting, and possible sensor faults. There is no widespread use of the current signal to make statements about the pump condition, although current sensors are installed in many applications anyway. As for motor fault diagnosis, different current-based techniques have demonstrated their function. Today, motor current signature analysis is used in industry, especially for the diagnosis of induction motors. In this thesis, the current-based diagnosis of typical pump-related faults in different applications is evaluated. In total, three different pump types are investigated: a wet-rotor pump, a dry-runner inline pump, and a submersible pump. The techniques used for motor fault detection are adapted for the diagnosis of pump-related faults. The results indicate that the faults clogging, impeller crack, and bearing wear, in particular, influence two frequencies in the current spectrum, which can be used as a basis for a condition-based maintenance strategy. Especially in wet-rotor pumps, these two fault indicators strongly vary depending on the hydraulic load point of the pump. With the help of a feature extraction method based on the adapted reference frame theory, this work demonstrates that the two frequencies can be analyzed in real time in a field environment. Furthermore, a concept for cloud monitoring is presented and validated with the help of a laboratory test. Additionally, it is demonstrated that the faults are visible if the starting current is evaluated in a time-frequency map, which has not been considered before in the literature on pump-related faults. In summary, the findings of this work indicate that current-based diagnosis methods can successfully detect typical faults in pumps, a fact that is of high interest for companies using these assets in their industrial processes.Becker, V. (2022). Current-based Techniques for Condition Monitoring of Pumps [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19063

Linear actuator for a submersible water pump for use in boreholes

Both the theory and the test results show that the E-core electromagnet linear actuator, which is based on the variable reluctance principle, can generate a normal force in excess of 400kNm(^-2) when there is a flux density of IT within the airgap. When the actuator is used as a driver in a submersible water pump for use in boreholes the results show that the pump is capable of pumping up to 90% of the expected value. Pressures in excess of 10 Bar have been achieved, whilst the pump was operating at frequencies up to 30Hz. The flow rate was less than 0.21s ', however improvements to the pumping system are given, and the desired 1ls ' flow rate is achievable at a delivery head of 100m.The use of linear actuators for use in submersible water pumps is a relatively new technology, and as the demand for safe clean water increases, it provides for sustainable development. The actuator utilises a D C. supply with solar panels as the source, giving the potential for global use, particularly in developing countries (the South).The design of the driver can be optimised for selected parameters. However, the development of such drivers does have limitations, the overall diameter of the pump is restricted to that of the bore-hole size, 4 or 6 inches; further the length of the pump is dictated by the straightness of the bore-hole. Consequently, design tools, for the design of E-core Variable Reluctance Linear Actuators, (VRLA), are given

Asset management in urban water utilities: Case study in India

Access to safe and sufficient drinking water and adequate sanitation are now recognized as basic human rights. One Millennium Development Goal is to reduce by half the proportion of people without access to safe drinking water and basic sanitation by 2015. However, ensuring sustainability of existing and new services is considered to be one of the major challenges for the water sector in the years to come. In India, in addition to service expansion, existing water service quality has been observed to be deteriorating over recent years. There is therefore an equally urgent need to address sustainability and improvement of service quality to the presently served population. In this low-income country, where water utilities are unable to recover even the service costs of operations and minor maintenance through user charges, there is a need to determine ways and means to be able to maintain a cost-effective service to consumers. For such a capital intensive service these ways have to include not only the introduction of efficiency measures but also the long-term planning of capital maintenance, that is the maintenance of the fixed assets upon which services depend. Water utilities in high-income countries have been using various fixed asset management techniques to improve asset operational efficiency, to plan capital maintenance and to demonstrate their ability to maintain and improve service to their customers. This study explores the viability of the application of asset management techniques and their potential contribution towards improving water service provision in urban centres in India. Following a literature review, a generic asset management model for a low-income country water utility was developed and then applied in the water utility serving Jaipur, Rajasthan to assess the viability of this adaptation. Having identified strengths and weaknesses during this fieldwork a revised model was proposed, including distinct phases of asset management/data intensity, which could be used as a generic approach in large urban centres in India. Following consultations with prospective users in six States, the study showed that it is feasible to take a first step towards asset management at low cost but this will require a change in the management approach. The study identified lack of relevant data as a key factor influencing an effective and comprehensive application of a generic asset management model. The study concludes that the proposed phased asset management models can contribute to improving serviceability for customers; however the concern that remains is the willingness of the organisation to adapt to the necessary changes

Data-driven prognostics for critical electronic assemblies and electromechanical components

The industrial digitalisation enables the adoption of robust, data-driven maintenance strategies that increase safety and reliability of critical assets such as electronics. And yet, an implementation of data-driven methods which primarily address the industrialisation of diagnostic and prognostic strategies is opposed by various, application specific challenges. This thesis collates such restricting factors encountered within the oil and gas industry, in particular for the critical electrical systems and components in upstream deep drilling tools. A fleet-level, tuned machine learning approach is presented that classifies the operational state (no-failure/ failure) of downhole tool printed circuit board assemblies. It supports maintenance decision making under varying levels of failure costs and fleet reliability scenarios. Applied within a maintenance scheme it has the potential to minimise non-productive time while increasing operational reliability. Likewise, a tailored and efficient deep learning data pipeline is proposed for a component-level forecast of the end of life of electromagnetic relays. It is evaluated using high resolution life-cycle data which has been collected as a part of this thesis. In combination with a failure analysis, the proposed method improves the prognostics capabilities compared to traditional methods which have been proposed so far in order to assess the operational health of electromagnetic relays. Two case studies underpin the need for tailored prognostic methods in order to provide viable solutions that can de-risk deep drilling operations. In consequence, the proposed approaches alleviate the pressure on current maintenance strategies which can no longer meet the stringent reliability requirements of upstream assets

Asset management in urban water utilities : case study in India

Access to safe and sufficient drinking water and adequate sanitation are now recognized as basic human rights. One Millennium Development Goal is to reduce by half the proportion of people without access to safe drinking water and basic sanitation by 2015. However, ensuring sustainability of existing and new services is considered to be one of the major challenges for the water sector in the years to come. In India, in addition to service expansion, existing water service quality has been observed to be deteriorating over recent years. There is therefore an equally urgent need to address sustainability and improvement of service quality to the presently served population. In this low-income country, where water utilities are unable to recover even the service costs of operations and minor maintenance through user charges, there is a need to determine ways and means to be able to maintain a cost-effective service to consumers. For such a capital intensive service these ways have to include not only the introduction of efficiency measures but also the long-term planning of capital maintenance, that is the maintenance of the fixed assets upon which services depend. Water utilities in high-income countries have been using various fixed asset management techniques to improve asset operational efficiency, to plan capital maintenance and to demonstrate their ability to maintain and improve service to their customers. This study explores the viability of the application of asset management techniques and their potential contribution towards improving water service provision in urban centres in India. Following a literature review, a generic asset management model for a low-income country water utility was developed and then applied in the water utility serving Jaipur, Rajasthan to assess the viability of this adaptation. Having identified strengths and weaknesses during this fieldwork a revised model was proposed, including distinct phases of asset management/data intensity, which could be used as a generic approach in large urban centres in India. Following consultations with prospective users in six States, the study showed that it is feasible to take a first step towards asset management at low cost but this will require a change in the management approach. The study identified lack of relevant data as a key factor influencing an effective and comprehensive application of a generic asset management model. The study concludes that the proposed phased asset management models can contribute to improving serviceability for customers; however the concern that remains is the willingness of the organisation to adapt to the necessary changes.EThOS - Electronic Theses Online ServiceGBUnited Kingdo