DeepsinAI has a more than 10 years of experience this type of industry:
Deesinai has huge industry experience with standard and widely recognised software packages, such as OFM, ECLIPSE, PROSPER, GAP, MBAL, PipeSim, RodStar, SubPump, WellFlo, PCP CFER.
- Data preprocessing nad processing
- Extracting relevant information from available data
- Application of a spectrum of algorithms with the best performance
- Deep learning models and traditional models of ML
- Computer vision
- Problems of supervised and unsupervised learning
- Models of contextual bandits
- Reinforcement learning
- Combinatorial optimization and numerical techniques
Machine Learning to Transform Oil and Gas Industry
Oil and gas industries are facing several challenges and issues in data processing and handling. Large amount of data bank is generated with various techniques and processes. The proper technical analysis of this database is to be carried out to improve performance of oil and gas industries. Machine learning models are only as good as the data that was used to train them. So MLOps always starts with the data. Using small amount of the quality data, data scientists and machine learning engineers will be capable to exploite useful information from raw data sources and transform oil and gas industry to the next level. Our data science expertise consists of spending the majority of time trying to source and wrangle the right data as well as select the right features for model training.
Big data in Oil and Gas industry
Oil and gas companies face the challenge of obtaining insight from an enormous amount of data to make better, more informed decisions. Handling this huge amount of data is a complex job that can be completely solved with experience team of big data engineers. Our big data team is focused on investing in data accessibility and quality capabilities, as well as providing data scientists with a convenient way to work with big data that can make a 10x difference in productivity and the accuracy of decisions.
Deep learning applied to Oil and Gas industry
Compared to traditional machine learning models, deep learning models can significantly increase prediction performances of algorithms that are applied in computer vision and signal processing. Our deep learning team is capable to apply and implement different types of algorithms for solving a wide variety of computer vision and signal processing problems observable in Oil and Gas industry in the aspect of production quality assurance and security.
Optimization and reinforcement learning
Many different downstream and upstream tasks in Oil and Gas industry are closely related to optimization, hence our team of professionals are highly experienced in application and implementation of different methods for solving control (reinforcement learning based) problems and onedimensional or multidimensional optimization tasks.