Petrophysical Machine Learning
The SPWLA 2022 Spring Topical Conference will focus on the Petrophysical Machine Learning. The committee encourages the SPWLA community to share both theories and applications of the emerging machine learning methods as applicable to the petrophysical research. We are seeking submissions on machine learning related research in the following subjects:
- Multivariate regression: such as properties prediction or synthetic logs.
- Supervised classification and unsupervised classification: such as rock and fluid typing, zonation, outlier identification, or depth alignment.
- Deep learning with high-dimensional data: such as CNN or RNN methods on sensor arrays, waveforms, images, or volumes.
- Frontier topics: such as energy transition applications in geothermal and carbon capture & storage, novel model design or training, denoise, or other new research topics related to petrophysics.
Keywords: Machine Learning, Deep Learning, Artificial Intelligence, Petrophysical Interpretation
CALL FOR ABSTRACTS Abstract submission deadline: 11:59pm CST Monday, January 31st, 2022
SUBMIT ABSTRACT HERE
Questions: [email protected]
DATE: March 23-24, 2022
LOCATION: 3000 N Sam Houston Pkwy E, Houston, TX 77032
VENUE: Halliburton North Belt Campus - Auditorium
Fees: Members $375, Non-Members $475, Students $75
Members in Transition $100.00: Request for this fee is required, email to [email protected] for more information.
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