CPQ Energy LLC was constituted as a legal entity in 2016 in Katy Fort Bend in Texas, US. Since then we have been riding the wave in being presently ready to provide specialized solutions in predictive modeling, business analytics, and data mining for several industries in the state of Texas.
Our initial offering targeted the Energy Sector but early on we broadened our offering to many other important industries. An interesting statement by Eric Emerson Schmidt, former Google CEO: "Between the origin of the Earth and 2003 five Exabytes1 of information were created; today that amount is created every two weeks...". Cited in Unsupervised Learning with R (Kindle Locations 266-267). Packt Publishing.
Therefore, we strongly believe that Data Mining and its associated disciplines Artificial Intelligence, Pattern Recognition, Machine Learning, Statistics and Database Systems SQL/NOSQL can provide a useful insight if we have to deal with huge amount of data to analyze. Note: 1 1 Exabyte = 1 Billion Gigabytes
dario h. romero MSc - reservoir engineer & data scientist
A highly-experienced leader in reservoir engineering, I possess a solid track record of making key contributions within the leading upstream oil and gas operator/service company, Schlumberger. With a well-honed ability to perform integrated reservoir studies, and application software to support field development evaluations. My expertise includes:
Supervised-Unsupervised ML Modeling – Oracle/MySQL/SQL Server & SSRS, MongoDB NoSQL -
R & Python - Surveillance & Diagnosis – Economics - Reservoir & Well Numerical and Analytical Modelling
Known as an excellent communication, problem-solver, trainer and mentor, I hold a MS in Computer Science from Simon Bolivar University, Caracas, Venezuela, and a BS in Geodetic Engineering from the University of Zulia, Maracaibo, Venezuela.
- Identified 138 potential candidates for re-fracking, re-connecting, and re-charging stimulated reservoir volume. BHP Billiton needed an evaluation of possible candidates for further simulation in vicinity of their own operated wells. Conducted data mining for 4850+ horizontal wells operated by 20+ companies to determine high-level potential candidates on West Eagle Ford. Analyzed well performance by using a parametric model, pivot tables and cluster analysis with unsupervised machine learning SOM algorithm. Successfully completed project, used for an in-depth analysis and determination of economic feasibility.
- Produced an Analysis on Reservoir Performance Signature for Unconventional Reservoirs. CPQ Energy researched on a way to rapidly identify potential opportunities for candidate recognition in wells operated by diverse companies. The Study adopted a Reproducible Research approach using R and several essential libraries. This Study shaped the basis of a paper “SPE-179994 Data Mining and Analysis - Eagle Ford Formation - South Texas” to be published on the next SPE/IAEE Hydrocarbon Economics and Evaluation Symposium in Houston TX 2016. http://rpubs.com/darioromero/152204
- Sentiment Analysis of Political Situation in Venezuela using Tweeter & Machine Learning. The main purpose of this study is to determine expressions of somebody's opinions, sentiments, emotions, affect, expressed through Twitter. The study proved to be a very good method to confirm the precary political and social situation in Venezuela which as of February 2016 is being governed by a socialist dictador Nicolas Maduro. The study showed up how the population is organizing by themselves to defeat the government in peace and democratically. The analysis has been published in RPubs and can be accessed for free here. http://rpubs.com/darioromero/154955
- Implemented water-flood production workflow for project monitoring, boosting productivity 30%. Full-scale workflow for advanced monitoring of startup projects was needed in Oman fields. Launched workflow process for PDO including on-site training, and consulting for engineers working on enhanced oil recovery projects. Deployed agreed-upon solution, reducing man-time 1 week per engineer for 60 engineers, with associated cost savings.
- Utilized unconventional workflow processes to analyze oil/gas shale reservoirs, growing market share 30-40%. Schlumberger Technology Corp. lacked a way to analyze unconventional shale/tight oil & gas reservoirs on a global basis, a handicap in boosting market share in production engineering solutions offering. Led effort and collaborated with Engineering and Product Management to find a solution, leading to 30% market growth in 2012 and 40% in 2013.
- Exploring the NOAA Storm Database - An Study to determine impact on our lives - A High Level and Broad Analysis. Study carried out using R and several packages for determining how severe weather events are able to explain its impact on U.S. economy as well as losses to human beings in terms of lives and injuries. Analysis was well received by peer reviewers and help to highlight workflows on how to analyze this type of events using R Statistical software. http://rpubs.com/darioromero/82635