The Signal and the Noise

Some time ago Zhiyong pointed me to Nate Silver's book "The Signal and the Noise" which is about the science of prediction. I'm now reading it again and in fact go back to it regularly because it is, I believe, essential (and sobering) reading for anyone engaged in the modeling business.

One of the key things I took away from this book is the human tendency to psychologically "anchor" on any scenario which we have put a lot of time and effort into constructing. This is a real danger for anyone who has toiled through the process of building a 3D model for a basin where much data gathering, entry, mulling over input parameters, resolving IT issues etc is often necessary to reach the point where the model can be executed. This typically takes days to weeks in my experience. Then, depending on the size of the model, it might take hours to days to complete a single run. At the end of this process one is well and truly "anchored" on the particular scenario chosen in the process of setting the model up. It is very hard, and very time consuming, to then go back and test alternative scenarios. It has been made easier by recent software and hardware improvements but it is still a difficult thing to do psychologically.

In training courses I am fond of a particular analogy for the model building process which involves some pictures of bridges. The idea is that any model is a framework of physical law that we use to connect the known (data, analogs etc) to the unknown (our target play or prospect). We need both good data and a good framework to build a good bridge and so get to the other side safely. In a way, the model algorithms encode prior knowledge (in the Bayesian sense) about how petroleum systems work in general, hopefully preventing us over-fitting our data and indulging in the wilder of our fantasies.

While reading the book last week an old and favourite movie appeared late one night on the TV. This was David Lean's classic 'The Bridge on the River Kwai", Alec Guinness in the lead role. For those who don't know this movie, the story describes a group of English prisoners in WWII Thailand, being forced by the Japanese to build a rail bridge over the river Kwai. The martinet colonel (Guinness) keeps his soldiers alive, in the face of appalling mistreatment, by giving them the focus of building the bridge. At the end of the movie the bridge is complete and the first Japanese train about to cross it. The British plan, all along, was to blow up the bridge with hidden charges just as the train crosses. However, when it comes down to it Guinness cannot bring himself to blow the bridge and tries to prevent it. He has become "anchored" to the bridge through the pain and toil of building it and is unable to see the "bigger picture" of hampering the Japanese war effort.

Happy Modeling

Using fluid inclusions to infer the presence of a paleo hydrocarbon column

Analysis of diagenetic fluid inclusions, whether by optical or chemical means, is a technique used to learn something about a petroleum system. The main utility is for old wells where no fluids samples are available and where all that remains may be some old cuttings in a store.

One of the best known methods is "fluid inclusion stratigraphy (FIS)" provided by Fluid Inclusion Technologies (FIT) in Tulsa, USA. FIS is one of many possible fluid inclusion analysis methods which can perhaps be grouped together under the term "Microshows".

A common question asked of fluid inclusion data is "Was there ever a hydrocarbon accumulation in my (now water wet) reservoir ?" In other words, is there a paleocolumn ?" The government research body in Australia (CSIRO) uses the "grains with oil inclusions (GOI)" method which involves counting the number of grains with oil inclusions visible through a microscope under UV light and expressing the result as a percentage (%GOI). CSIRO suggests a threshold of 3.5% GOI as the minimum consistent with a paleocolumn. From calibration studies in one province my company set a similar threshold for the FIS paraffin response some years ago.

Any comparison between optical and chemical indicators of fluid inclusion "strength" is difficult. For both practical and theoretical reasons we would not expect a simple relationship between the two. For one thing, an optical method such as %GOI counts the frequency of grains with visible oil inclusions whereas FIS measures the concentration of volatile hydrocarbons (and other species) released by crushing a bulk sample. Obviously, if the sample has a few big inclusions it would give a smaller GOI and larger FIS signal cf. one with a lot of small inclusions. There are several other reasons why the measures are not equivalent. However, we would at least hope that they would give the same answer to the question of paleocolumn presence or absence.

The figure below shows the results of a comparison for 49 samples from 9 wells. In all cases, where GOI indicated a paleocolumn FIS agreed. Similarly in most cases where GOI indicated no paleocolumn, FIS agreed. However, there were a few samples where FIS indicated a paleocolumn and GOI did not. From the location of these samples (all from one well) and the signal character it is likely that this is a paleo-gas condensate zone and hence the optically detectable oil inclusions are rare. This comparison is for one particular province and I cannot warrant that it would work out this way for other geological circumstances. 

So what does all this mean for evaluation of a petroleum system ? Clearly if we found that the target reservoirs in dry holes had high fluid inclusion abundance we might conclude that trap breach rather than lack of charge was the reason for failure. If the abundance is high enough we could carry out further analysis to permit oil-source or gas-source correlation to confirm activity of the prognosed source rock or the presence of a previously unrecognised one. We would hope to be able to do this on simple extracts of the cuttings (rather than on the tiny amounts in fluid inclusions)  but this isn't always feasible due to loss during storage or severe contamination with drilling mud.