... Abstract We present an integrated system that automatically collects historical and current data from heterogeneous sources, performs analytics to identify telltale signatures of Loss of Containment (LOC) events, and makes asset behavior predictions as an asset ages. Our semantically enhanced...

... applications which are increasingly pushing the frontiers to improved uncertainty modelling. uncertainty analysis Artificial Intelligence Upstream Oil & Gas machine learning reservoir characterisation prediction deterministic model neural network caer Exhibition reservoir uncertainty...

... Abstract The objective of this paper is to integrate "Big Data" concept with petroleum engineering knowledge for the prediction of recovery factor in Deepwater Gulf of Mexico (dGOM) oilfields. Recovery factor is affected by many geological and engineering factors; as a result...

... employs a fast and accurate mathematical model to predict flow and formation properties profiles in advanced completion wells. It also introduces specific measurement response functions for numerical simulation of permanent downhole gauge data in the advanced wells. The inversion model employs a modified...

... Abstract Many production and injection wells completed with intelligent (smart) systems are operating around the world. These wells are more economical and efficient than conventional wells. Computational tools for predicting bottomhole flowing pressure and temperature can provide valuable...

... in one cluster as pump failures when reports had to be made due to wells being shut in. This information is sufficient to label one of the clusters as healthy and the other one as faulty. For a new measurement, a prediction may be made by first determining the cluster to which the measurement belongs...

... Abstract The demands placed on operators to effectively manage production operations become more complex and challenging with increasing numbers of high recoverable oil and gas fields in frontier environments (remote onshore, deepwater and ultra- deepwater). Predicting flow rates of wells...

... Abstract The importance of performance monitoring is growing as the number of high-pressure, high-temperature (HPHT) wells continues to increase in deepwater and ultra-deepwater fields. Accurate prediction of HPHT well performance is essential for enhancing deepwater oil and gas production...

... nonparametric methods are used to estimate probability density/mass functions to characterize the uncertainty in the properties estimated through analogous reservoirs. We perform experiments to assess both the quality of property prediction and the quality of the selected analogues. We report results produced...

... in unconventional multi-phase reservoirs. Two forward-acting models and two inverse-acting models were developed. The forward-acting models predict oil, water and gas production profiles (and bottom-hole pressure profile for flow rate-specified wellbore conditions) for any given well design with parameters within...

... of the RF’s independent variables based on a collection of uncertainty runs. In the exploration and production (E&P) applications, DT has been used extensively; appraising, real option valuation selecting an artificial lift method, predicting permeabilities and detecting fracture corridors. However...

... operations are mentioned. The approach has been tested on a North Sea reservoir. An interconnected suite of models for reservoir pressure, indication of the presence of gas coning, virtual flow measurement for fluids and gas production, and dynamic prediction for future fluids and gas rates, was developed...

...-called grey-box approach which combines a physical model and artificial intelligence. The two approaches are applied to the problem of predicting the bottom-hole pressure during a managed pressure drilling operation to demonstrate the improved accuracy and robustness. ensemble approach physical...

... properties are used by the well stability model for RT predictions. A multi-purpose geo-pressure modelling tool which includes all significant processes relevant to pressure generation and dissipation is coupled to the integrated drilling simulator and can give updated pore pressure predictions during...

... workflow society of petroleum engineers spe intelligent energy conference pressure difference real time system production monitoring downhole pressure prediction machine learning artificial intelligence production control neural-network model flow metering drillstem/well testing choke...

... wireless technology to capture more measurements has significantly increased the volume of data available. This wealth of data put BP in an even better position to leverage predictive analytics technology. The technologies’ data-driven approach has many advantages over the traditional trending or first...

... parts of the system feeding an enhanced predictive maintenance capability. Mechanistic models of a production system are themselves complex and challenging to use and maintain. Normally their use is restricted to modelling experts primarily for design purposes or to support troubleshooting following...

... & gas hydrocarbon process asset management operation real time system maintenance platform disruptive event prediction innovation reliability knowledge management collaboration information History: asset management and collaboration in the oil and gas industry Recognizing...

... Abstract Short-term production optimization relying on model-based predictions over a short period (weeks to months) requires the use a near-borehole reservoir model. Such a model is usually developed and validated through standard well testing. Standard well testing has to be repeated...

... in the physical model, which results in a more accurate prediction of the mud flow out of the well, and subsequently fewer false kick alarms. production control Artificial Intelligence production monitoring flow metering well control Upstream Oil & Gas Simulation mud density information alarm...