The goal of Teics is to form recommendations for particular measures to be taken for wells which will for sure lead to a growth / stabilization of oil production, to stabilization / reduction of water cut in brownfields. In certain cases we don’t only propose a measure, but also make its quantitative assessment, e.g. indicate the volume of the chemical used. See the whole list of our recommendations.
FIELD DEVELOPMENT AND MACHINE LEARNING
MLM
Solving tasks of clusterization and regression
Engineering logics
Steps of computations
INSIM
Physical model based on the material balance and Buckley-Leverett theory
Machine learning models can be successfully applied if there is a credible experience in the past. As input, the model uses both design data and data obtained during direct measurements. Teics’s fine work includes a careful selection of high quality past experience, computation of some input data using common physical models (INSIM, etc.) and setting of machine learning models. For us, it is obligatory to check the adequacy of obtained forecasts, and compliance of mathematics with the physical processes which we intended to describe and predict from the beginning. All our experiments are already in the past. Now we just increase production using the method created.
During the whole history – once, during the pilot project – on a weekly basis
Routes and coordinates
During the whole history – once, during the pilot project based on drilling facts
Monthly data, operational report
During the whole history – once, during the pilot project – on a monthly basis
Well logging, dynamic well testing
During the whole history – once, during the pilot project – on a monthly basis
Implemented repairs and well intervention techniques
During the whole history – once, during the pilot project – on a weekly basis
Teics tries to use the whole set of field historical data. However, due to various reasons, information is not always present in the full amount. That’s why our requirements are rather suggestions. We are ready to discuss possibilities of work with data which are available. You can download the list and prepare to pilot tests in advance; in such a way you will significantly speed up the start of our cooperation and will approach the results of production much sooner.
FIELD DEVELOPMENT AND MACHINE LEARNING
In Teics, all development tasks are divided into 10 large steps. Of course, our division
is conventional, and many steps are closely connected to one another. However, such point of
view on development helped to create a solution with high practical results. It may help to
.increase oil production in your fields as well
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