Data-Driven optimization of intermittent gas production in mature fields assisted by deep learning and a population-based global optimizer

In gas wells, decreased/unstable production can occur due to difficult-to-predict dynamic effects resulted from late-life phenomena, such as liquid loading and flooding. To minimize the negative impact of these effects, maximize production and extend the wells’ lifetime, wells are often operated in an intermittent production regime. The goal of...

Data-driven detection of well events in mature gas fields

The production optimization of mature gas fields is severely complicated by the occurrence of certain undesired well events such as salt precipitation, liquid loading, or gas/water coning. Learning from production data of periods in which such events have taken place could help operators improve the process optimization. However, due to the...

Informed production optimization in hydrocarbon reservoirs

The exploitation of subsurface hydrocarbon reservoirs is achieved through the control of production and injection wells (i.e., by prescribing time-varying pressures and flow rates) to create conditions that make the hydrocarbons trapped in the pores of the rock formation flow to the surface. The design of production strategies to exploit these...

Quantification of the impact of ensemble size on the quality of an ensemble gradient using principles of hypothesis testing

With an increase in the number of applications of ensemble optimization (EnOpt) for production optimization, the theoretical understanding of the gradient quality has received little attention. An important factor that influences the quality of the gradient estimate is the number of samples. In this study we use principles from statistical...

Extended Brugge benchmark case for history matching and water flooding optimization

The Brugge benchmark case designed for the SPE Applied Technology Workshop (ATW) held in Brugge in June 2008 has proven to be valuable for testing and comparing methods of history matching, production optimization and closed-loop optimization by its extensive use in literature. Key features that contributed to its usefulness for history matching...

Smart Dairy Farming Aanpak Requirements-analyse (Eisen en Wensen): Persona’s en UseCases

Het doel van het project Smart Dairy Farming (SDF) is het ondersteunen van melkveehouders bij de verzorging van individuele dieren, om daarmee een goede gezondheid, een langer leven en een langere productietijd van de koe te bewerkstelligen. Daartoe ontwikkelt Smart Dairy Farming sensoren en andere technologische hulpmiddelen, beslismodellen,...

Smart Dairy Farming Aanpak Requirements-analyse (Eisen en Wensen): Persona's

Het doel van het project Smart Dairy Farming (SDF) is het ondersteunen van melkveehouders bij de verzorging van individuele dieren, om daarmee een goede gezondheid, een langer leven en een langere productietijd van de koe te bewerkstelligen. Daartoe ontwikkelt Smart Dairy Farming sensoren en andere technologische hulpmiddelen, beslismodellen,...

Smart Dairy Farming Aanpak Requirements-analyse (Eisen en Wensen)

Het doel van het project Smart Dairy Farming (SDF) is het ondersteunen van melkveehouders bij de verzorging van individuele dieren, om daarmee een goede gezondheid, een langer leven en een langere productietijd van de koe te bewerkstelligen. Daartoe ontwikkelt Smart Dairy Farming sensoren en andere technologische hulpmiddelen, beslismodellen,...

Smart Dairy Farming Aanpak Requirements-analyse (Eisen en Wensen): SDF Eisen en Wensen 1.0

Het doel van het project Smart Dairy Farming (SDF) is het ondersteunen van melkveehouders bij de verzorging van individuele dieren, om daarmee een goede gezondheid, een langer leven en een langere productietijd van de koe te bewerkstelligen. Daartoe ontwikkelt Smart Dairy Farming sensoren en andere technologische hulpmiddelen, beslismodellen,...

Ensemble based multi-objective production optimization of smart wells

In a recent study two hierarchical multi-objective methods were suggested to include short-term targets in life-cycle production optimization. However this previous study has two limitations: 1) the adjoint formulation is used to obtain gradient information, requiring simulator source code access and an extensive implementation effort, and 2)...

Real-time intelligent production monitoring of a North Sea asset

The increasing complexity of natural gas extraction because of reducing reserves, complex behavior and more intricate contractual rules (due to liberalization of the West European energy markets) creates a need for more effective production efficiency. In order to deal with these challenges Wintershall is realizing a real-time monitoring system...