Predicting Stuck Pipes during Drilling

The problem of stuck pipes accounts for several billions of dollars worth of non-productive time for oil & gas operators each year. Developing a method to predict this event in real-time has become high priority for the drilling industry. Automatically predicting stuck pipe events is now possible due to modern sensor techniques and advanced data analysis tools.

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Signal Identification in Particle Physics

Experiments in particle physics face the problem of identifying elementary particles produced at frontier energy colliders. Typical colliders have millions of channels of electronics, producing terabytes of data per second. These data are analyzed in real time and reduced to a few terabytes per day that is stored for later analysis. Of the billion particle collisions occurring each second, only a few are of interest. Finding these interesting -but possibly unanticipatedcollisions in such a massive data stream represents a challenging test of forefront technology and computational power.

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Pattern Recognition Enables  Creating Maps of Mars Landforms

To develop a robust system for the automatic geomorphic mapping of land surfaces using a fusion of pattern recognition tools, including machine learning, computer vision, and data compression

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Data Analytics for Computer Systems Management

The ability to predict service problems in computer networks, and to respond to those predictions by applying corrective actions brings multiple benefits. First, detecting system failures on a few servers can prevent the spread of those failures over the entire network. For example, low response time on a server may gradually escalate to technical difficulties on all nodes attempting to communicate with that server.

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Deep Learning: Enhancing your Predictive Models with High Level Representations

Traditional data mining algorithms attempt to search for a predictive model by looking at raw variables that often bear little correlation with the class for prediction.

As an example, predicting stuck-pipes during drilling can be extremely complicated when one looks at raw variables that exhibit high interactions and carry little relevant information on their own.

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Automatic Assistants to Select Data Mining and Machine Learning Techniques

Data mining and machine learning techniques have become pillars during the analysis of massive amounts of data. Such fields of study have generated hundreds of different algorithms for generation of predictive models, finding patterns in data, automatically classifying objects or events into new categories, etc.

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Predictive Analytics

Our times are characterized by an unprecedented flood of data streams, together with a lack of efficient tools to extract useful pieces of information from massive data repositories. Applications such as credit rating, medical diagnosis, machine failure prediction, fraud detection, and identification of astronomical objects in images, generate thousands of instances for analysis at an unprecedented rate, outpacing the technology needed for proper analysis and interpretation.

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For more in-depth views of Artificial Intelligence subject and its applications please follow this link to Professor Vilalta publications.


Noesis provides state-of-the-art computational techniques for data analysis, business analytics, and decision making.

Noesis incorporates methods from artificial intelligence, signal processing, and pattern recognition, to analyze massive amounts of data and uncover its hidden value.

Our technology stands out from other existing solutions by incorporating cutting-edge state-of-the art techniques that are just coming out from the research community allowing for uncovering hidden value not available to others.

Our solutions combine sophisticated statistical tools that bring expert domain knowledge into the analysis phase. Our models are not just data driven but also model driven. We ensure solutions that correspond to real patterns amenable to analysis and interpretation.

Noesis provides many services including consulting work in the use of modern data analysis and data mining techniques; generation of predictive models for forecasting and prediction, with solutions tailored to the particular needs of each client; personalized courses in advanced data mining and pattern recognition; and computational tools for strategic decision making.


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Houston, TX

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