Our client, a medium size oil company, wanted to minimize the number of BOP test. The
reason was that in case of leakage, people went into ad-hoc mode of problem solving,
with the result of high NPT (non productive time). Management felt that optimization
technology could bring a solution to the table if it is possible to derive the minimal
number of additional tests needed in case of leakage.
reason was that in case of leakage, people went into ad-hoc mode of problem solving,
with the result of high NPT (non productive time). Management felt that optimization
technology could bring a solution to the table if it is possible to derive the minimal
number of additional tests needed in case of leakage.
Checking leakage in a Blow Out Preventor network
Blowout Preventers (BOPs) and choke manifolds are key pieces of drilling rig equipment to prevent the
uncontrolled release of potentially hazardous formation fluids to surface. The blowout prevention testing
problem is that of testing BOP valves to check if they are functional or not. A decision model allows for a
structured and time saving approach to minimize the number of test sets in order to identify leakage.
uncontrolled release of potentially hazardous formation fluids to surface. The blowout prevention testing
problem is that of testing BOP valves to check if they are functional or not. A decision model allows for a
structured and time saving approach to minimize the number of test sets in order to identify leakage.
Prior to developing the decision model it was believed by many practitioners that applied mathematics
could not help. We present this client result story, as it is a striking example that demonstrates that
analytics and optimization technology can provide huge business value.
could not help. We present this client result story, as it is a striking example that demonstrates that
analytics and optimization technology can provide huge business value.