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In this chapter, we get acquainted with a powerful log interpretation technique that not only helped early log analysts find water saturation from a very limited set of log measurements but also set an example for later developments both in logging tool design and in formation evaluation. The pioneer, Maurice Tixier, cleverly saw that if a calculation required an unknown parameter the need for it could be sidestepped by the simple expedient of taking ratios of known or measured parameters. The principle can even be applied to find porosity from a compensated thermal neutron log by taking the ratio of the near and far count rates. The absolute counts depend on both porosity and the unknown effects of hole size and mud weight, but the ratio of the two is practically unaffected by anything but porosity. Tixier’s seminal paper was published in 1949 and has certainly stood the test of time.

This chapter covers the manual methods used with pre-digital well logs to determine connate water resistivity, Rw, and the rock matrix (zero-porosity) responses of the main “porosity” tools, namely the sonic, neutron, and density. Today these two parameters are derived from plots that are regularly run as subroutines in preinterpretation passes that automated interpretation packages offer. However, the analyst of yesteryear, working with paper prints, was obliged to build these plots manually using graph paper and laboriously reading pairs of log readings, plotting them, and then constructing the required trend lines that, hopefully, pinpointed the required parameter, which could then be used in the main calculations of formation porosity and water saturation.

Due to the complexity of finding formation porosity from the original “count rate” neutron tools that topic was covered in detail in Chapter 5. Now we turn our attention to all that followed the pioneering neutron logging tools and address the epithermal neutron tools and the compensated, (dual-detector) thermal neutron tools. In this chapter, we also provide a perspective of all the many combinations and permutations of the types of radioactive source, atomic particles propagated and detected, and the number of detectors and their spacings as used in what we may call the nuclear logging “zoo.”

In this chapter, the special case of running and interpreting logs recorded in empty, that is, air-drilled, holes is discussed. Practical guidelines are given for quantitative analysis using the pre-digital logs that were available at the time these analysis techniques were developed and put into practice.

Quick-look methods, by definition, allow the log analyst to find useful petrophysical formation properties without having to make any numerical calculations. This chapter summarizes several such methods as they were used in the pre-digital era. Many are based on visual comparison of analog curves on a paper log print. Some of these methods are still in use today, others have been forgotten but are worthy of being documented here because they will show up in the files of the pre-digital archives. Compatible overlays of analog curves mirror the philosophy of taking ratios to eliminate unknowns and were made use of widely in times gone by—but they still have their place today.

A typical complete sedimentary cycle involves five phases (pre-erosional, in transit, post-depositional pre-burial, post-burial, exhumation) and six processes potentially modifying the original composition of the sediment. Some processes add mineral species to an assemblage, others subtract minerals, and yet others can both add and subtract minerals; moreover, some can operate in only one of the five phases, whereas others can affect up to three phases. Authigenic growth and anthropogenic addition are relatively easy to recognise and compensate for, occurring in predictable and limited environmental conditions. Although mechanical weathering can substantially alter heavy mineral assemblages, its effects also are predictable, and prolonged or intense abrasion is required. In contrast, differential sorting of minerals during transport can have a rapid and profound modifying effect on a heavy mineral assemblage that is less readily compensated for but does broadly follow the laws of physics. In an analogous effect, any contrasts between heavy mineral studies in the size fraction selected by each analyst can seriously undermine data comparison. The widely recognised boundary between superficial pedochemical weathering and deeper geochemical weathering is largely artificial. Both phenomena frequently and often profoundly modify heavy mineral assemblages, but the resulting patterns of depletion vary considerably. For example, intrinsic properties of minerals conferring vulnerability to acid pedochemical weathering include well-developed multiple cleavage planes and/or inclusions, high-energy lattices and high Fe 2+ content. However, these properties are insufficient to accurately predict a stability series in any particular heavy mineral assemblage, as both relative and absolute depletion rates are strongly influenced in the post-depositional environment by both abiotic factors (e.g., pH, redox potential) and under-researched biotic factors. Five case-studies of heavy mineral assemblages in British Tertiary and Quaternary deposits are used to illustrate these principles and to demonstrate the benefits of (a) using multivariate methods to elucidate patterns of variation in heavy mineral assemblages, (b) characterising a weathering front using 90% depletion ( D 90 ) values and (c) integrating heavy mineral data with those derived from other geoanalytical and field-based techniques. This approach allows not only more accurate reconstruction of provenance but also of palaeoenvironments; both can then usefully inform correlation.

Any phylogenetic study inevitably includes many precepts—assumptions that must be accepted a priori if the ideas of greatest interest are to be developed satisfactorily. The key precepts of this paper are as follows: 1. The distribution of morphological character-state transitions across the topology of a cladogram is biologically meaningful. In particular, it can be used to discriminate among contrasting evolutionary mechanisms possessing the potential to explain the inferred pattern, of character-state transitions.