Method and system for determining well delivery contributions using artificial intelligence

A system, comprising:

• a drilling system coupled to a wellbore;
• and
• a well operations manager comprising a computer processor and coupled to the drilling system, wherein the well operations manager comprises functionality for:
• obtaining well operation data regarding a plurality of well operations for a well delivery, wherein the plurality of well operations are performed by a plurality of service entities at a first well site;
• determining a contribution weighting factor using a machine-learning model and the well operation data, wherein the contribution weighting factor corresponds to a contribution of a first service entity among the plurality of service entities toward the well delivery;
• determining, using the contribution weighting factor and an adjusted weighting factor, a first plurality of performance indicator values for the first service entity, wherein the adjusted weighting factor is a weighting factor that is modified based on a size of the contribution weighting factor;
• and
• transmitting, based on the first plurality of performance indicator values, a first command to a second well site to change the first service entity to a second service entity for performing one or more well operations,
• wherein the plurality of well operations are selected from a group consisting of:
• inserting a casing into a wellbore at the first well site;
• pumping cement slurry into the wellbore and cementing the casing;
• producing a predetermined perforation at one or more locations within the wellbore using a bullet gun perforation technique, an abrasive perforation technique, or a water jet perforation technique;
• pumping a gravel slurry between the casing and a side of the wellbore;
• and
• installing a production tree on a wellhead of the wellbore.

A non-transitory computer readable medium storing instructions executable by a computer processor, the instructions comprising functionality for:

• obtaining well operation data regarding a plurality of well operations for a well delivery, wherein the plurality of well operations are performed by a plurality of service entities at a first well site;
• determining a contribution weighting factor using a machine-learning model and the well operation data, wherein the contribution weighting factor corresponds to a contribution of a first service entity among the plurality of service entities toward the well delivery;
• determining, using the contribution weighting factor and an adjusted weighting factor, a first plurality of performance indicator values for the first service entity, wherein the adjusted weighting factor is a weighting factor that is modified based on a size of the contribution weighting factor;
• and
• transmitting, based on the first plurality of performance indicator values, a first command to a second well site to change the first service entity to a second service entity for performing one or more well operations,
• wherein the plurality of well operations are selected from a group consisting of:
• inserting a casing into a wellbore at the first well site;
• pumping cement slurry into the wellbore and cementing the casing;
• producing a predetermined perforation at one or more locations within the wellbore using a bullet gun perforation technique, an abrasive perforation technique, or a water jet perforation technique;
• pumping a gravel slurry between the casing and a side of the wellbore;
• and
• installing a production tree on a wellhead of the wellbore.