DATA-DRIVEN ANALYTICS  PARA INGENIEROS DE PETROLEO , PETROFÍSICOS Y GEOCIENTÍFICOS

DEEPAK DEVEGOWDA, PH.D  THE UNIVERSITY OF OKLAHOMA

ASSOCIATE PROFESSOR, GRADUATE LIAISON & MEWBOURNE CHAIR IN PETROLEUM ENGINEERING #1

COSTO: US$ 475.00

( I NCLUYE I MPUESTOS)

Pagos a cuenta SPE Lima (en dolares) Para depósito o transferencia BBVA es: 0011 0508 0100004072 93 (De BBVA a BBVA y/o depósito en ventanilla) Para CCI (Código interbancario) es: 011 508 000100004072 93 (De otros bancos a BBVA) Pagos online: http://bit.ly/EIAcheckout

CONTACTO PERÚ Ana L. Sandoval | [email protected] Tel: 2422455 | Cel: 948251820 OKLAHOMA Yoana Walschap | [email protected] 

Noviembre 9-10, 2018 HORARIO NOV. 9 DE 1 PM – 8 PM NOV. 10 DE 8:30 AM – 8 PM

Universidad Nacional de Ingeniería (UNI). Unidad de Posgrado de la Facultad de Ingeniería de Petróleo, Gas Natural y Petroquimica Sector D1. Altura del puente peatonal del Metropolitano Lima, Peru

Auditorio

DATA-DRIVEN ANALYTICS  PARA INGENIEROS DE PETROLEO , PETROFÍSICOS Y GEOCIENTÍFICOS Noviembre 9-10, 2018

Universidad Nacional de Ingeniería (UNI). Unidad de Posgrado de la Facultad de Ingeniería de Petróleo, Gas Natural y Petroquimica, Sector D1. . Altura del puente peatonal del Metropolitano, Lima, Peru

Curso en Ingles Participantes requieren laptop

DEEPAK DEVEGOWDA, PH.D  Associate Professor in the Mewbourne School of Petroleum and Geological Engineering at the University of Oklahoma. His research interests lie in the areas of understanding, modeling and management of unconventional oil and gas reservoirs, enhanced oil recovery, high-resolution reservoir description, and geostatistical reservoir characterization. He PERÚ Ana L. Sandoval | [email protected] 2422455 | Cel: 948251820 earned hisTel: Ph.D. degree and M.S degree, both in Petroleum Engineering at Texas A&M University. OKLAHOMA Yoana Walschap | [email protected] 

DATA-DRIVEN ANALYTICS FOR PETROLEUM ENGINEERS, PETROPHYSICISTS AND GEOSCIENTISTS

INSTRUCTOR: Dr. Deepak Devegowda, Associate Professor, Mewbourne School of Petroleum and Geological Engineering, University of Oklahoma INTRODUCTION Have you ever wondered how Google or Amazon target you for advertisements? Or how do you identify treatments for cancer patients based on gene expression? Or even how do you get approved for credit? How is your insurance premium determined? Is this e-mail spam? Data Mining/Data Analytics provides most of the answers to these questions and has enormous potential for the geosciences. Recent advances in machine learning and availability of computational power have accelerated the analyses and interpretation of rich, heterogeneous data from both real-time and legacy datasets. These include production, drilling and completions data, SCADA data streams, geologic analyses, 3D and 4D seismic, well data such as cores, well-logs, thin-sections and images. This 2-day course introduces the theory and applications of data mining/data analytics in the geosciences. As such it will be of immense value to petrophysicists, geologists, geophysicists, petroleum engineers and managers who want to extract meaning out of their data. Specifically, after completion of this course, the attendees will be able to apply the tools learnt to several of their own problems and interpret (and even question) the results of commercial products. 1. 2. 3. 4. 5.

Some of the more novel applications of such techniques include: History matching of production data for reservoir characterization Reservoir characterization using seismic, well log or core data or a combination of these. Understanding the governing controls on well productivity including completion, geologic or petrophysical variables. Predicting lost time drilling incidents ahead of time, such as stuck-pipe or lost circulation among others. Diagnosing and predicting artificial lift failure, such as with ESPs from SCADA data.

COURSE OBJECTIVES and SCHEDULE This course will cover the theory and applications for some of the more popular data mining/statistical learning algorithms present. The course is very hands-on. You will learn the theory and then apply these tools to real field datasets to develop your own insights. The list below is not comprehensive but provides a flavor of what you can expect:

OU Energy Institute of the Americas | Mewbourne College of Earth and Energy | The University of Oklahoma. Address | Sarkeys Energy Center: 100 E Boyd St. Room 1510. Norman, OK 73019 | [email protected]

AGENDA CURSO DATA-DRIVEN ANALYTICS  DÍA 1     TIME                                             ACTIVITY                                        1 - 1:15 pm

Welcome and Introductions

1:15 - 2 pm

Introduction to Data Mining, Analytics and Machine Learning

2 - 3 pm

Introduction to Univariate and Multivariate Statistics

3 - 3:30 pm

First Coffee Break

3:30 - 5:30 pm

Linear, Ridge, Lasso Regression

5:30 - 6 pm

Second Coffee Break

6 - 8 pm

Unsupervised Classification: K-Means, Self Organizing Maps, Heirarchical Trees

DÍA 2     TIME                                             ACTIVITY                                        8:30 - 10:30 am

Case Studies: Unsupervised Classification

10:30 - 10:45 am

Morning Coffee Break

10:45 am - 12:45 pm

Supervised Classification: Support Vector Machines, Random Forests

1 - 2  pm

Lunch

2 - 3 pm

Case Studies: Supervised Classification

3 - 3:30 pm

First Afternoon Coffee Break

3:30 - 5:30 pm

Artificial Neural Networks and Applications

5:30 - 6 pm

Second Coffee Break

6 - 8 pm

Deep Learning and Applications 

8 pm

Closing remarks. End of Course