International Conference on
Oil and Gas

The O&G industry has been for years relying on knowledge more than information, in recent years the collapse of the O&G prices lead to major savings and new ways to operate. As we seen this, IIoT, ML, M2M, Analytics and AI has stepped forward looking for information to be, not only ahead of the market and be able to produce more or less according to the market demands, but having a safer operation costing less that previously, improving the O&M costs and having better knowledge of what is going on in the wells, the fields, the operation facilities, the personnel, the transportation, the structural integrity, the wear and operability of moving parts and the corrosion of pipes and tanks among others. The goal of a project of IIoT, ML, M2M, BI, BA or AI has to have a clear goal, What are the sources of information to achieve that?, the project must answer the questions that at this moment cannot be answered with the information we have or reduce the uncertainty of the main variables to make a decision, for example when to do the maintenance of the pumping units in a pipeline, we must do it as the manual of the equipment? Or before the parts fail? What is the optimal cost and safety mix that apply to the company, market, politics…? If we delay the maintenance how that will affect the operational costs Vs maintenance costs and Vs the safety of the personnel? How about the energy costs? How this affects the whole chain? The operations must get to the optimal point of operation, whatever this means to the company, for a certain company would be energy efficiency, for other, will be global O&M cost efficiency and the technology will help with this, the companies don’t need to have them all, but choose the one that will add to the strategical need of the company.