Comments (1)
Hello Martin,
Thank you very much for taking the time to read my contribution and commenting. I regret the delay in responding: I've only just stumbled upon this.
The link between depth and geocomputing is essential, whenever well data is involved, because depth is the cross-referencing field for each data set, each data set has its own depth measurement, but frequently we ignore this last point and assume that all the depth measurements are the same. When we do that and start computing, we combine ill-matched data sets, resulting in noisy-to-completely-invalid calculations.
Analogy: consider the two vectors X = (x1, x2, x3, x4, x5, x6, x7, x8, x9, x10) and Y = (y1, y2, y3, y4, y5, y6, y7, y8, y9, y10), and consider the computation X+Y. What we want is: X+Y = (x1+y1, x2+y2, x3+y3, x4+y4, x5+y5, x6+y6, x7+y7, x8+y8, x9+y9, x10+y10), but if what we frequently do through carelessness / poor training is: X + Y = (x1+y3, x2+y4, x3+y5, x4+y6, x5+y7, x6+y8, x7+y9, x8+y10, x9+y11, x10+y12). In this analogy, the vectors X and Y represent 2 logs, and the element index represents the depth index.
Geocomputing involving well data at any point relates to depth in that good depth is a critical but often overlooked pre-requisite.
I'm happy to review the article to make this more explicit. I have actually not looked at it since writing it 2 years ago.
Again, thank you.
from 52things.
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