...-heuristic optimisation searching speed of an enhanced algorithm with the robustness of fuzzy logic reasoning; based on the degree of membership functions rather than exact or extreme conditions, and the learning capability of neural networks, to derive the required intelligence. This allows a predictive...

... intelligence algorithms (which include genetic algorithms, artificial neural networks, Bayesian networks amongst others) in reservoir uncertainty modelling, which now points to a future of using more sophisticated machine learning systems for achieving reservoir models and parameters with higher confidence...

... analytics genetic algorithm production workflow big data Saputelli Upstream Oil & Gas Exhibition statistical technique application intelligent operation production optimization analytic technique neural network algorithm reservoir Introduction Information technology...

... and gas saturation at the grid block level. The results demonstrate that this technique is capable of generating the reservoir simulation output very accurately within seconds. Modeling & Simulation machine learning reservoir simulation neural network Artificial Intelligence Pattern...

... performance analyses barely capture the complex interaction between these well structures and the reservoir. Therefore, this paper discusses the application of artificial neural network models to forecast production from advanced well structures, and well designs for field deployment of these well structures...

... of workflows that embrace data management facets as well as diverse data mining modules established under the banner of soft computing or artificial intelligence. When does one implement a neural network, a decision tree or non-linear regression techniques? Will Genetic Algorithms or Fuzzy Logic be appropriate...

... that (a) data mining and neural networks are by far the most popular AI technologies used in the industry; (b) approximately 50% of respondents declared they were somehow engaged in applying workflow automation, automatic process control, rule-based case reasoning, data mining, proxy models, and virtual...

... and proved successful in all the trails carried out after this field trial. This paper will address the methodology of the new approach and highlight the importance of planning and implementing the drilling parameters in realtime. neural network bit wear compliance artificial intelligence strength...

... workflow. To address this problem, a new workflow using a set of predictive proxy models has been developed that combines artificial intelligence techniques such as neural networks with nodal analysis, and sporadic and high-frequency data to allow engineers to process and understand production behavior...

... automation adoption corporate culture neural network miller engineer artificial intelligence measurement and control information 000-hour rule intelligent energy psychology intelligent-energy solution process control and automation upstream oil & gas maslow mastery overload motivator...

... for measuring individual well-oil production based on a neural network and online correlation logic using data from sensors, well tests, and simulations. This system permits a closer right-time monitoring of the wells by enabling readings to be taken more frequently and by minimizing the intrinsic estimation...

... Abstract Determining injector-producer relationships, i.e., to quantify the inter-well connectivity between injectors and producers in a reservoir, is a complex and non-stationary problem. In this paper, we present a neural-network-based sensitivity analysis approach to address this problem...

...-driven applications Some studies have successfully identified potential for recovery improvement Neural Network applications have successfully identified potential for injection/production optimization information management machine learning Artificial Intelligence Upstream Oil...

... rate prediction neural network ESN sensitivity presentation machine learning Reservoir Surveillance annular pressure drilling alarm system neuron flow model integrating experience threshold value society of petroleum engineers real time system petroleum engineer Pump Rate real-time...

... simulator genetic algorithm chromosome reservoir simulation well pattern neuro-fuzzy system modeling & simulation neural network neural network asset and portfolio management Introduction The main task of reservoir engineering team is to develop a plan to recover as much hydrocarbon...

...-to-date results from studies on statistical theory in recent decades even recent years are firstly applied to EOR potentiality analysis. The applications of group method of data handling (GMDH), Improved BP artificial neural network, and support vector machine (SVM) are discussed. The comparison...