Banca de QUALIFICAÇÃO: LUCAS BARBOSA DE MEDEIROS

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : LUCAS BARBOSA DE MEDEIROS
DATE: 21/07/2023
TIME: 10:00
LOCAL: Videoconferência
TITLE:

Anomaly Detection System for Chromatographic Readings to Enhance Analytical Precision in the Context of Mud Logging.

KEY WORDS:

Chromatography, Mud Logging, Machine Learning.

PAGES: 42
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUMMARY:

The detection of anomalies in chromatographic readings improves the accuracy in identifying chromatographic peaks of relevant chemical components in mud samples, aiding in decision-making and enhancing the oil exploration process. The proposal presented here aims to work on the development and validation of an efficient algorithm for the detection of chromatographic peaks in the context of mud logging, as well as the development of a methodology capable of extracting a standardized numerical representation that can be subjected to Machine Learning models. This methodology represents a step of Feature Engineering and has the ultimate goal of allowing the detection of anomalies in the analyzed samples. Building upon the results obtained with the peak detection module, it is expected that the extraction of the standardized numerical representation provides relevant information about the data quality. The initial results of the peak detection algorithm implemented in Python demonstrated an efficiency above 90% in peak detection, even in situations with noise and amplitude variations.

COMMITTEE MEMBERS:
Presidente - 2566657 - SAMAHERNI MORAIS DIAS
Interno - 1577068 - KURIOS IURI PINHEIRO DE MELO QUEIROZ
Externo ao Programa - 2757086 - JOILSON BATISTA DE ALMEIDA REGO - UFRN