Abstract
Abstract
The estimation of wellbore position uncertainty, sometimes referred to as error modelling, is of vital importance when considering the safety and efficiency of the drilling process, particularly in crowded fields with tight spacing between wells. New survey tools employing new technology, new principles and sophisticated data processing techniques become available every year with different accuracy claims. The dependability of the error models and whether they properly represent the uncertainties of a given survey system, new or old, is not easy to judge. This paper describes a simple method to support the validation process of uncertainty models.
Multiple surveys of different type are often available for the same well with some degree of overlap for different wellbore sections. For example, the well might have been drilled using magnetic MWD data and later a drop gyro might have been run to reduce the positional uncertainty or to validate the magnetic data. Overlapping surveys can be compared, and the difference can be gauged against the claimed uncertainty models using the relative instrument performance model (RIP) test and the Chi-square test.
Analysis of several wells with different trajectories and more than 100 overlapping surveys has allowed a major oil company to build confidence and accept the uncertainty models claimed by one service company. This has allowed the oil company to implement the service company IPM (Instrument Performance Model) files without having necessarily to understand in great detail how the survey systems operate, how they are calibrated or quality controlled. Using the right models allows optimal planning of wells and survey programs, and reduces the risks of a collision while at the same time permitting wells to be drilled in congested fields.
The paper describes a simple approach for validating uncertainty models for survey tools. The tests used for the validation are available in most well planning software programs and can be completed by personnel without the necessary expertise required to understand the subtleties of all the survey tools involved in the process.
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