System and method for controlling artificial lift units

A method of controlling a plurality of artificial lift units at a plurality of wellsites, the artificial lift units including reciprocating rod lift units, the artificial lift units having installed controllers, installed sensing equipment, and installed communication systems, the method comprising:

• interfacing distributed processing equipment with the installed controllers and the installed communication systems at the plurality of the wellsites;
• connecting the distributed processing equipment together in one or more networks;
• obtaining, at the distributed processing equipment, operating parameters of each of the artificial lift units from the installed sensing equipment at the wellsites in real time;
• analyzing, with modelling functions of the distributed processing equipment, trends of the operating parameters of at least the reciprocating rod lift units of the artificial lift units by monitoring balance of the reciprocating rod lift units of the artificial lift units;
• predicting, with automated machine learning of the distributed processing equipment, conditions of at least the reciprocating rod lift units of the artificial lift units based on the analyzed trends by predicting deleterious operation of the reciprocating rod lift units in out-of-balance conditions leading to damage of the reciprocating rod lift units based on the monitored balance, the deleterious operation requiring a manual correction;
• determining, with the distributed processing equipment, at least one temporary automated control configured to counteract the predicted conditions of at least the reciprocating rod lift units of the artificial lift units by determining adjustments to the reciprocating rod lift units to counteract the out-of-balance conditions as a remedial correction at least until the manual correction is performed;
• and
• regulating output of an actuator of each of the reciprocating rod lift units to adjust a pumping speed configured to counter the out-of-balance conditions by implementing the at least one temporary automated control with instructions communicated from the distributed processing equipment to the installed controllers of at least the reciprocating rod lift units.

A system for controlling a plurality of artificial lift units at a plurality of wellsites, the artificial lift units including reciprocating rod lift units, the artificial lift units having installed controllers, installed sensing equipment, and installed communication systems, the system comprising:

• communication equipment having network interfaces in communication with one or more networks and having local interfaces in communication with the installed communication systems;
• and
• distributed processing equipment in communication with the communication equipment, the distributed processing equipment installed at the plurality of the wellsites for the artificial lift units, the distributed processing equipment being configured to:
• obtain operating parameters of each of the artificial lift units from the installed sensing equipment at the wellsites in real time;
• analyze, with modelling functions of the distributed processing equipment, trends of the operating parameters of at least the reciprocating rod lift units of the artificial lift units, wherein to analyze the trends for the reciprocating rod lift units, the distributed processing equipment is configured to monitor balance of the reciprocating rod lift units;
• predict, with automated machine learning of the distributed processing equipment, conditions of at least the reciprocating rod lift units of the artificial lift units based on the analyzed trends, wherein to predict the conditions for the reciprocating rod lift units, the distributed processing equipment is configured to predict deleterious operation of the reciprocating rod lift units in out-of-balance conditions leading to damage of the reciprocating rod lift units based on the monitored balance from the analyzed trends, the deleterious operation requiring a manual correction;
• determine at least one temporary automated control configured to counteract the predicted conditions of at least the reciprocating rod lift units of the artificial lift units, wherein to determine the at least one temporary automated control for the reciprocating rod lift units, the distributed processing equipment is configured to determine adjustments to the reciprocating rod lift units to counteract the out-of-balance conditions as a remedial correction at least until the manual correction is performed;
• and
• implement the at least one temporary automated control with instructions communicated from the distributed processing equipment to the installed controllers of at least the reciprocating rod lift units to regulate output of an actuator of each of the reciprocating rod lift units to adjust a pumping speed configured to counter the out-of-balance conditions.

For a plurality of artificial lift units at a plurality of wellsites, the artificial lift units including reciprocating rod lift units, the artificial lift units having installed controllers, installed sensing equipment, and installed communication systems, a non-transitory programmable storage device having program instructions stored thereon for causing distributed processing equipment to:

• interface the distributed processing equipment with the installed controllers and the installed communication systems at the plurality of the wellsites;
• connect the distributed processing equipment together in one or more networks;
• obtain, at the distributed processing equipment, operating parameters of each of the artificial lift units from the installed sensing equipment at the wellsites in real time;
• analyze, with modelling functions of the distributed processing equipment, trends of the operating parameters of at least the reciprocating rod lift units of the artificial lift units, wherein to analyze the trends for the reciprocating rod lift units, the distributed processing equipment is configured to monitor balance of the reciprocating rod lift units;
• predict, with automated machine learning of the distributed processing equipment, conditions of at least the reciprocating rod lift units of the artificial lift units based on the analyzed trends, wherein to predict the conditions for the reciprocating rod lift units, the distributed processing equipment is configured to predict deleterious operation of the reciprocating rod lift units in out-of-balance conditions leading to damage of the reciprocating rod lift units based on the monitored balance from the analyzed trends, the deleterious operation requiring a manual correction;
• determine, with the distributed processing equipment, at least one temporary automated control to counteract the predicted conditions of at least the reciprocating rod lift units of the artificial lift units, wherein to determine the at least one temporary automated control for the reciprocating rod lift units, the distributed processing equipment is configured to determine adjustments to the reciprocating rod lift units to counteract the out-of-balance conditions as a remedial correction at least until the manual correction is performed;
• and
• implement the at least one temporary automated control with instructions communicated from the distributed processing equipment to the installed controllers of at least the reciprocating rod lift units to regulate output of an actuator of each of the reciprocating rod lift units to adjust a pumping speed configured to counter the out-of-balance conditions.