Oilwell casing perforation has been used in the industry since 1932 and was pioneered by the Lane-Wells Company who introduced the bullet-gun perforating technique. Shortly after the introduction of the bullet gun, explosive jet perforators were introduced, which provided a different and more aggressive way to perforate casing.

With the increased demand for oil and gas over the past decades, operators have been forced to explore deeper, hotter reservoirs to find the most prolific reservoirs. These deepwater opportunities have required constant changes to equipment and services to increase their technical capabilities for performing in more critical environments. Perforating with higher-shot densities, propellants, and larger perforating guns has been ongoing to meet these new challenges.

A major problem with these increases, however, is the difficulty in predicting dynamic wellbore behaviors that cause tubulars to collapse and bend and packers to unset as perforating guns were detonated. Research to understand the pressure behavior during the perforation event, in addition to the solid loading that is imparted to the tubulars, packers, and other completion hardware in the perforating assembly, was needed to enable the industry to go forward with a high level of confidence that wells could be completed safely and cost effectively.

This paper discusses a shock-wave computer modeling program that evaluates the mechanical risk factors of well components to ensure that the health, safety, environment, and service quality needs in a design are addressed. A time-marching, finite-differences technique is applied as the numerical method for both fluids and solids. The software is installed on a personal computer and typically executes the models within several minutes to several hours, depending on the complexity of the job design.

The physics-based model has been validated (Schatz et al. 1999 and Schatz et al. 2004) with special high-speed recorders that sense pressure, temperature, and acceleration at a sampling frequency of 115,000 samples per second.

This paper provides data from offshore oil and gas wells in the Gulf of Mexico to demonstrate the success of the design.

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