Accuracy enhancement · MSA

Multi-Station Analysis

MSA estimates systematic sensor corrections from measurements across several survey stations.

What MSA estimates

Multi-Station Analysis (MSA) uses measurements from several survey stations to estimate systematic errors in a directional sensor package. These include axis biases, scale-factor errors, and non-orthogonality.

A single station can support checks of gravity magnitude, magnetic field strength, and dip. These checks cannot determine a full calibration. Some sensor errors pass these limits while still causing inclination or azimuth errors.

A calibration applies to an interval where the error pattern is sufficiently stable. Temperature changes, shock, or drift can change that pattern during a run. The analysis must then assess whether one calibration remains suitable.

How sensor errors change the measurements

An ideal three-axis sensor measuring a constant field places every possible orientation on a sphere centred on zero. The following drawings show conceptual projections of that measurement surface.

Ideal triad
An ideal sensor measuring a constant field maps all orientations onto a sphere centred on zero.
Bias
Axis biases shift the centre of the sphere.
Scale factor
Unequal axis scale factors produce an ellipsoid. Equal scale changes on all axes preserve a sphere with a different radius.
Non-orthogonality
Non-orthogonal axes can shear the surface. A rigid rotation preserves a sphere.

Conceptual projections for a constant field. Each triad has nine basic error terms: three biases, three scale factors, and three non-orthogonality terms. The joint model can include alignment and reference offsets. Limited orientations can leave terms coupled or poorly determined.

Bias shifts the surface. Unequal scale factors and non-orthogonal axes can deform it. A rigid rotation preserves the sphere, so field magnitude alone cannot determine every alignment correction.

Real survey stations sample only part of the surface. Similar inclinations or toolfaces can leave parameters coupled or poorly determined. More stations with similar orientations do not necessarily resolve these limits.

How the analysis works

The analysis compares each station with its reference gravity magnitude, magnetic field strength, and dip. The reference values can vary with location, depth, and time.

TALLENTECH uses joint nonlinear estimation with robust residual weighting. The model includes nine basic sensor error terms per triad: three biases, three scale-factor errors, and three non-orthogonality terms. It also supports relative accelerometer–magnetometer alignment and constrained magnetic field-strength and dip offsets.

The selected configuration determines which parameters vary, remain fixed, or use prior constraints. A fitted parameter set is not proof of one uniquely determined physical calibration.

The magnetic reference follows the selected survey-processing source. This can include a main-field model, IFR1, or IFR2. Reference uncertainty remains part of the analysis. Declination is needed to convert magnetic azimuth to true azimuth.

Robust weighting reduces the influence of some large residuals. It does not guarantee detection of every bad measurement. Review the station flags, weights, excluded data, and solver status before accepting a correction.

Before-and-after residuals show agreement with the fitted constraints. Smaller residuals do not, by themselves, prove more accurate inclination or azimuth. Parameter resolution, remaining uncertainty, and independent checks also matter.

Axial accelerometer check shots

Downhole survey stations give MSA little information about the axial accelerometer. Its bias (Gz bias) and scale-factor error are hard to resolve from downhole data, and both affect inclination and TVD.

Surface check shots isolate them. The rig takes surveys with the tool vertical, at 0° and at 180° inclination. The axial accelerometer then reads about +1 g and about −1 g. Half the sum of the two readings gives the bias. Half the difference, compared with local gravity, gives the scale-factor error. MSA solves these check shots separately. It then holds the axial bias and scale-factor error at the measured values when it fits the downhole stations.

The check shots give each tool's actual values, instead of the generic allowance of 0.4 mg (1σ) for the bias. A bias that is not corrected tilts the calculated path. On a horizontal lateral, each 1 mg of bias tilts it by about 0.06°, which moves the well about 3 m vertically over 3,000 m. The bias also reaches dip and azimuth: see how a Gz bias reaches inclination, dip and azimuth.

An illustrative uncertainty comparison

Figure 1 uses TALLENTECH's uncertainty engine and generic error models on the published ISCWSA standard test well #1. It compares reference-model, MSA and check-shot assumptions at a total measured depth of 8,000 m. The displayed 2σ values are uncertainty half-widths.

FIG. 1Figure 1,ISCWSA #1 · 2σ · modelled
Figure view
Well direction
CaseEngine code2σ LAT2σ VERTStep change
Five-yearly low-resolution modelMWD+LRGM202.0 m45.3 mBaseline
MWD+HRGM182.0 m45.3 m−10% LAT
MWD+IFR1166.9 m45.3 m−8% LAT
MWD+IFR1+MS86.7 m45.3 m−48% LAT
MWD+IFR1+MS, ABZ/ASZ reduced85.7 m45.1 m−1% LAT · −0.5% VERT
Overall, first to last−58% LAT · −0.5% VERT

Select a case to draw its step: the case above in amber, this case in blue.

NoteIn this modeled east–west case, azimuth sensitivity to axial magnetic interference limits the reduction from a lower reference uncertainty.

For the published direction, the IFR1-to-MSA step reduces the lateral half-width from 166.9 m to 86.7 m, about 48%. In the turned N–S case, it changes from 73.9 m to 53.7 m, about 27%. This step changes magnetometer terms only, so the vertical half-width remains 45.3 m.

The last step adds the Gz check shots. In the error model, the allowance for the axial accelerometer bias falls from 0.4 mg to 0.1 mg (1σ), and the allowance for its scale-factor error from 0.05% to 0.04%. The vertical half-width falls to 45.1 m in both directions. In the published direction, which runs nearly magnetic east–west, the lateral half-width also falls slightly, from 86.7 m to 85.7 m: there, an axial bias also moves the long collar azimuth.

That change is small. Uncertainty terms add in quadrature, and BHA sag and tool misalignment dominate this well's vertical uncertainty. Figure 2 shows the terms at TD: the check shots reduce the 2.2 m axial bias term to 0.55 m, and the 22.7 m total (1σ) changes by only about 0.1 m.

FIG. 2Figure 2, Vertical at TD: what the ellipse adds, and what a bias doesISCWSA #1 · MD 8,000 m

Uncertainty terms, 1σ · they add in quadrature

  • BHA sag, not corrected: 20.1 m
  • Tool misalignment: 9.4 m
  • BHA sag, after sag correction: 8.1 m
  • Axial accelerometer bias, model allowance 0.4 mg: 2.2 m
  • Axial accelerometer bias, after check shots 0.1 mg: 0.55 m
  • All terms, IFR1 and MSA: 22.7 m
  • All terms, IFR1, MSA and sag correction: 13.2 m

Shift of the calculated TD · not an uncertainty

  • 0.5 mg bias, not corrected: 2.7 m
  • 1 mg bias, not corrected: 5.4 m
  • 2 mg bias, not corrected: 10.8 m

SourceTALLENTECH uncertainty engine, ISCWSA MWD Rev5 error model, on the published ISCWSA #1 test well at TD (horizontal). Terms are the engine's vertical breakdown; other terms are 2.7 m or less. Shifts are by minimum curvature with every inclination changed by the bias. A positive bias makes TD deeper; a negative bias makes it shallower.

The ellipse includes an uncorrected bias only as the 0.4 mg allowance (1σ), combined in quadrature with the other terms. An actual bias does not add in quadrature; it moves the whole well by its full amount. On this well, each 1 mg of axial bias moves the calculated TD about 5.4 m vertically. After sag correction, the vertical total at TD is 13.2 m (1σ), so a bias of that size is a large part of what remains. The check shots measure the bias of each tool, so MSA can remove the shift.

The step changes in Figure 1 are modeled uncertainty changes, not measured correction accuracy. In this example, the MSA step halves selected magnetometer bias and scale-factor terms and reduces the axial interference term.

The benefit depends on the well direction, measurements, reference uncertainty, and remaining errors. A good residual fit alone does not justify a reduced error model. Its use needs applicable quality checks and evidence for the remaining uncertainty.

Correction limits and quality checks

MSA can estimate systematic sensor errors and stable tool-axis magnetic interference patterns. In one run, an axial sensor bias and drillstring interference can contribute to the same fitted offset. The fit does not necessarily separate their causes.

Some configurations can estimate constrained field-strength and dip offsets. They cannot independently establish all reference-field errors. Declination errors need external information. BHA sag and measured-depth errors also need separate treatment.

Referencing, MSA, and sag correction address different errors. Select their combination from the well conditions, available data, and processing requirements.

Poor residual agreement can result from unsuitable reference values, changing sensor errors, bad measurements, or limited measurement geometry. Numerical convergence only means the solver met a stopping condition. Review the fit quality and warnings separately.

Record the accepted correction, its valid interval, input references, solver configuration, and application status. Include the available parameter-resolution and uncertainty information. Keep the basis for any reduced uncertainty model with the definitive survey records.

References

Deliverables

What you get.

  1. 01Accepted sensor corrections with their valid intervals and application status
  2. 02Corrected inclination and azimuth with before-and-after residuals and station quality flags
  3. 03Input references, solver configuration, and available parameter-resolution and uncertainty information
  4. 04Records to support survey review and the basis for uncertainty-model selection
FAQ

Common questions.

Q.01What data does MSA need?

MSA needs Gx, Gy, Gz and Bx, By, Bz readings with their units, axis conventions, and sensor identity. It also needs station locations and reference values. Time-dependent references need survey timestamps. Different tool orientations can improve parameter resolution. More stations at similar orientations do not guarantee a stronger calibration.

Q.02Can MSA rescue a failing tool?

MSA can estimate stable systematic sensor errors. Erratic failures or changing errors can make one fixed calibration unsuitable. Residuals and quality flags can show a problem, but further checks may be needed. Review the result before applying a correction.

Next step

Send us one well.

Tell us about one well. We reply within 24 hours, and once the raw sensor data arrives we review it and tell you what we find.