Multi-Station Analysis (MSA) is a technique widely used in MWD directional surveying to provide additional quality control and to correct for systematic errors. Although the method's potential to enhance survey quality has been demonstrated through several publications, experience has shown that MSA can produce unstable solutions and poorly interpretable results. In such cases, it is likely that the uncertainty estimate assigned to the data is invalid. Unfortunately, there is no standard in the oil industry defining the correct use of MSA. Different companies have developed different requirements and acceptance criteria, making it difficult to judge and compare survey quality between companies. The industry should therefore seek to establish a common standard for the application of MSA.

This paper presents a set of fundamental requirements that have to be fulfilled in order to ensure the correct application of MSA in drilling operations. The requirements consist of a set of mathematical rules and corresponding acceptance limits. Survey quality can be verified against any MWD error model by using the same mathematical framework, but changing the acceptance limits. Requirements and acceptance criteria are presented for two specific error models: Basic MWD without axial interference correction (Williamson 2000) and the same model assuming enhanced geomagnetic referencing.

The results presented in this paper show which systematic errors can be estimated for any given data set. A mechanism for determining tolerable survey noise is also included. This prevents misapplication of MSA under poor surveying conditions such as magnetic storms and drill-string vibration. The objective has been to develop requirements that are easy to apply in operations and which can form the basis for standardization across the industry.


Multi-Station analysis (MSA) is a more powerful survey quality evaluation method than conventional single station calculations (Ekseth et al. 2006). It makes it possible to identify and quantify different types of systematic errors, providing greater proof of whether or not surveys meet specification (see e.g. Brooks et al. 1998). Where systematic errors of significant magnitude are identified they can be corrected for. However, the ability of MSA to correct failed surveys and provide increased confidence that surveys meet their stated specification is limited by several factors. For example, only a limited number of systematic error terms can be estimated accurately for a given set of survey data, this being dependent on factors such as the geometry of the wellbore, the number of survey stations and the number of estimated error terms, see e.g. Nyrnes et al. (2005), Nyrnes and Torkildsen (2005); Torkildsen et al. (2004). In current common practice, it is not always clear how the application of MSA to a given survey log affects its status with respect to its own accuracy specification. Improved accuracy may be claimed, but the link between MSA data manipulation and the error model that quantifies accuracy is usually not explicit.

In this paper, a basic MSA methodology suitable for adoption across the industry is proposed. The methodology consists of a set of requirements and acceptance limits that have to be fulfilled when applying MSA. The requirements can be applied to any survey log to determine which error terms can be validly estimated. In addition, mechanisms are included to ensure that the random noise level in the survey data is of tolerable magnitude. The requirements are easy to apply and straightforward to implement, and should therefore be easily communicated throughout the survey industry. An earlier version of the MSA requirements was presented and discussed at the 26th SPE WPTS (former ISCWSA) meeting in November 2007 (Nyrnes et al. 2007).

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