Abstract:
Described herein are systems and methods for evaluating and mitigating the wax risks of a given hydrocarbon composition such as crude oil. The disclosed systems and methods enable rapid and ready prediction of wax risks using algorithms based on a small sample of the hydrocarbon composition. The wax risks are predicted using predictive models developed from machine learning. The disclosed systems and methods include mitigation strategies for wax risks that can include chemical additives, operation changes, and/or hydrocarbon blend.
Abstract:
A water treatment system comprises an electrolytic cell comprising: a first electrode; a second electrode comprising a coating of polymer comprising structural units of formula I and a power source for powering the first and the second electrodes; wherein R1 is independently at each occurrence a C1-C6 alkyl radical or —SO3H; R2 is independently at each occurrence a C1-C6 alkyl radical; a is independently at each occurrence an integer ranging from 0 to 4; and b is independently at each occurrence an integer ranging from 0 to 3. An associated method is also described.
Abstract:
A water treatment system comprises at least one electrolytic cell comprising at least one electrode and a power source for powering the electrode. The electrode may be a metal electrode comprising a coating of polymer comprising structural units of formula I (I) wherein R1 is independently at each occurrence a C1-C6 alkyl radical or —SO3M wherein M is independently at each occurrence a hydrogen or an alkali metal a hydrogen or an alkali metal, R2 is independently at each occurrence a C1-C6 alkyl radical, a is independently at each occurrence an integer ranging from 0 to 4, and b is independently at each occurrence an integer ranging from 0 to 3. An associated method is also described.