Current types of axial excitation tool have been shown to produce beneficial results — in terms of load transfer to the bit, general reductions in string friction and reductions in drill dysfunctions — such as stick slip.

The positioning of such tools to achieve optimum benefit is therefore extremely important — in order to maximize the axial excitation to the areas of the string that require a reduction in friction, and also to minimize the axial excitation to the surface and to sensitive string tools (such as MWD) — where damage may occur.

This paper describes a string model that allows the position of axial excitation tools to be assessed — in terms of the string response — both locally and remotely from the tool.

The model breaks the string down in to springs and masses — with 10 nodes in the upper string; and 5 nodes in the BHA. Additional components can also be added to the string — such as shock tools, jars and accelerators — in terms of mass and stiffness.

The equations of motion are used to connect the nodes in terms of differential equations.

The model is Mathcad based, and as a result, executes very quickly — so allowing comparative studies to be carried out with relative ease.

Data input into the model is also achieved quickly.

The speed with which the model can be used lends itself to fine tuning input data.

The model has been compared with and ANSYS spring mass model, and good agreement has been reached.

Additionally, the model allows more than one axial excitation tool to be added to the string — in order to gauge the benefits of such a configuration.

Damping can also be varied at different locations in the string model.

The results from this model have been used to compare with field test data — derived from a string with instrumentation tool located at various points in the string.

The results show that good agreement can be reached between the model and the field test results, however, careful consideration needs to be taken of the damping assumed in the model.

The model can, never the less, be used for comparative studies — i.e. tool location, number of tools and optimum frequencies.

Further work is recommended in comparing model results with field test results — in order to get a better understanding of the effect of damping.

The damping model could be improved in the model presented here, or alternatively, the lessons learned here could be merged into an existing string model.

This content is only available via PDF.
You do not currently have access to this content.