... new insight from combining highly diverse data sources. We propose a novel machine-learning algorithm for semantic segmentation of rock matrix, fractures, vugs, and secondary mineralogy. After implementing and examining deep and shallow-learning approaches, we concluded to use shallow machine...

... in a dedicated PVT lab, an improved prediction of the fluid properties during pump-out, especially for LWD services, is required. Considering the limited real-time bandwidth available, the evaluation must be performed downhole. Therefore, new fluid type algorithms that combine multiple sensor readings into one...

... optimization (HO), has been developed for effectively optimizing the completion design of multilateral wells that are equipped with multiple types of FCDs. Differential evolution (DE), a metaheuristic optimisation algorithm, is utilized for initial exploration of the search space to identify promising regions...

... & gas artificial intelligence pipe geometry operation norway government ndt probe integrity brace splash subsea zone testing robot automated non-destructive weld inspection algorithm petroleum engineer society Introduction Jacket lifetime calculations are based on very long service...

... quantification geological subdiscipline roundness interpretation cement particle reservoir characterization connectivity particle moderately grain compacted information algorithm cementation cement content Introduction Reservoir properties is one of the main controls on prospectivity in oil...

... is crucial for early detection, but manual assessment is challenging due to the subtle nature of these anomalies and the analysis of video footage might take hours. This work aims to automate the inspection of flexible pipeline twisting by proposing an algorithm that processes video data obtained from...

... of determining the best supervised machine learning algorithm to incorporate to reduce the sensor offset problem. The bulk density and porosity logs are predicted at the bit in this paper using petrophysical and drilling parameters. The results of the model will be used to perform lithology identification...

... by conventional approaches. The purpose of this paper is to propose a knowledge-data hybrid approach and build a reliable and easy-to-use tool to automatically detect kicks. Based on the knowledge of the kick main indicators, this work utilizes Long-Short moving window average algorithm combining advanced...

... occur when key parameters deviate from safe operating conditions, leading to downtime and loss of production volumes. To address this challenge, the objective is to establish repeatable frameworks for constructing predictive models through the utilization of deep learning algorithms. These models...

... as a primary variable. We first implement a new phase-split algorithm with input variables as pressure and enthalpy instead of the usual pressure and temperature and we validate it on several test cases. This algorithm can model situations where the mixture can change rapidly from one phase to the other...

... Abstract This paper will present a software that was developed to diagnose well test data. The software monitors the data, and through a series of algorithms alarms the user in case of discrepancies. This allows the user to investigate possible source of errors and correct them in real time...

... of machine learning solutions in the industry, and particularly a shift towards more accessible in-house analytical capabilities. shorttext field machine learning structureless text Work Order verification algorithm Upstream Oil & Gas category distance metric operator dataset pareto...

... Abstract There are significant trends in the reduction of traditional 2D design, this is being replaced by the sole development of 3D models. This paper will detail how to develop algorithms to automate large aspects of a design review. These techniques significantly increase efficiency, ensure...

... is to better understand the feasibility of these methods, and to demonstrate the benefits of robotic inspection with regard to improving safety and efficiency, enhancing data capture and reducing operational costs. An object detection model was developed based on high-performance open source algorithms...

... Upstream Oil & Gas inventory level analytical method service level algorithm inventory analyst stock level architecture asset and portfolio management inventory optimisation tool inventory management spare part inventory optimisation society of petroleum engineers Introduction...

... if autonomous routing of drilling fluids could be done using advanced algorithms through a simple user interface. The idea was to design something as powerful and simple to use as a car navigation system, in that the source (i.e. car's position) is known, the destination can be entered and thereafter a route...

... survey accuracy new algorithm algorithm equation spe 166563 survey method rig time north south static mwd survey MWD survey Abstract When kicking off at low inclination, static measurement-while-drilling (MWD) surveys are used to confirm the kickoff direction when free of magnetic...

... field in Nigeria ( Ong et al. 2009 ) and the qualification of multiphase meters in viscous flows (see Atkinson et al. 2000 ). The algorithms used for reconstructing and predicting flow rate and WC, which are the focus of this paper, are not independent of the flowmeters and are used to complement...

... This approach guaranties a closer and faster collaboration between the different disciplines involved in a reservoir study because the feedback coming from the history match can be potentially incorporated into the structural, static and dynamic model. Several algorithms have been developed, most...

... drilling data algorithm spe 123785 exhibition petroleum engineer Introduction Formation evaluation is a key component of reservoir characterisation in which a variety of subsurface data are combined to provide estimates of reserves. The range of data available for formation evaluation varies...