Robert C. Ransom

What are Archie’s Basic Relationships

What is Meant by the Plot of *R*_{t} versus *S*_{wt}*ϕ*_{t}

Parallel Resistivity Equations Used in Resistivity Interpretation

What is the Formation Resistivity Factor

How is Exponent *n* Related to Exponent *m*

Observations and Conclusions from Figure 10 about Exponent *n*

Are There Limitations to Archie's Relationships Developed in this Model?

**Table of Retrievable Contents:**

**OBSERVATIONS AND CONCLUSIONS FROM FIGURE 10 ABOUT EXPONENT n**

Examine the curves drawn in **Figure 10**.

All calculations of exponent *n* shown in **Figure 10** are based on triangle CDG of the model in **Figure ****1**. Triangle CDG is the graphic depiction of the dual-water Archie two-exponent water saturation Eq. (4b).

The values of the calculated *n* from the logic of triangle CDG in the model and from Eq.(4b) are summarized in the type curves drawn in **Figure 10**.

**How to Interpret Figure 10**. Caution. Do not think of the curves in Figure 10 as profiles.

Each type curve represents a relationship between exponent *n* and saturation *S*_{wt} in a specific reservoir bed or same sample of rock at a deep radial depth beyond the invaded zone.

Imagine each of the curves as a series of smoothed bar graphs for exponent value of *n* over a full range of water saturations at a constant value of *R*_{t} . At any specific water saturation, the *n* value at that water saturation represents the degree of, or the effectiveness of, the interference by oil to the flow of electrical survey current in oil-wet- or water-wet rocks.

Not all of the chart is applicable. The values of exponent *n* are meaningful only at oil saturations greater than irreducible oil saturation. The values of *n* can be calculated in the region of irreducible oil and in the flushed zone only if the appropriate *R*_{t} is known and employed.

The curves are applicable only where a constant value of *R*_{t} remains valid. The curves are not valid where water saturations are high remains and exponent *n* is steep because a high value of *R*_{t} cannot be supported at high water saturations. At high values of water saturation, exponent *n* will begin a decline and continue to decline as water saturations increase until it reaches the value of exponent *m* . In Figure 1, resistivity *R*_{t} also will decline along with the decline of *n* until it reaches the value of *R*_{0 }.

As a result, the steep upward mathematical sweep of *n* values probably does not exist in nature. The high values of *n* can be calculated, but at high values of water saturation *R*_{t} must ultimately return to *R*_{0 }, thus *n* will return to *m*.

One of the first things to be observed in **Figure ****10** is that in both Zones A and B in Wells 1 and 2, as the resistivity gradient described by exponent *n* increases, predicted water saturation increases and the predicted oil saturation decreases. And, where the oil saturation is the greatest, exponent *n* is the lowest. Puzzling? This is in precise conformity with the prediction by *n* illustrated by slope CG of triangle CDG in **Figure ****1**.

For example:

1. If the voids in the rock are filled to a high oil saturation, an increase of 10% oil will decrease the volume of electrically conductive water correspondingly.

2. If the voids in the rock are filled to a low oil saturation, an increase of 10% oil will displace the same bulk volume of water as at high saturations.

3. Wherever the oil phase is continuous, whether at low saturations or high saturations, the electrical interference caused by adhesive insulating oil films on the pore surfaces will be nearly the same.

4. Although the electrical interference by oil in items 1 through 3, immediately above, is the same wherever the oil exists in a continuous phase, Figure 10 and the model in Figure 1 illustrate that the effectiveness is not the same.

5. The effectiveness of the interference by oil is greater at higher water saturations than at lower water saturations as seen by the increased values of *n*. This phenomenon is corroborated by the model in Figure 1, Equation (4b), and the type curves in Figure 10.

**In Figure 10 what do the curve crossovers mean at point H? Figure 10** illustrates that everywhere oil is present, the true value of exponent *n* is greater than exponent *m*, but some calculated values of *n* are lower than *m*. Why?

The calculated oil saturation is highest where exponent *n* approaches exponent *m*. In both **Figure ****1** and **Figure ****10** that maximum calculated oil saturation level is seen at point H. In Zones A in Wells 1 and 2, that maximum occurs at about 90% oil saturation (disregarding irreducible water saturation) where the curves for Zones A meet the assumed value of 1.6 for exponent *m*.

In **Figure ****10**, because the *n* curves for Well 1 Zone A and Well 2 Zone A, intercept the value of *m* at high oil saturations, it would imply that there is more oil to be produced from this reservoir. For Zone B, the highest oil saturation that can be calculated is about 50% where the curves for zones B also meet the value of exponent *m* at a point H. This behavior is illustrated in **Figure ****1** where line CG (slope *n*) of triangle CDG collapses to line CH that represents slope *m*. Any calculated value of *n* lower than the value of *m* is imaginary.

**What about the imaginary values of n in Figure 10?** The oil saturation where the calculated

Exponent *n* is higher in Zone A than in Zone B at the same water saturation in both wells. It can be seen in Figure 10 there is no mathematical relationship between exponent *n* and *S*_{wt} observed between one bed and another at any constant saturation value.

As *R*_{t} changes, the slope representing values for *n* might or might not change. Exponent *n* can vary independently of water saturation. For the value of *n* to increase above that of *m*, it is necessary only for oil to be present. Water saturation influences *n*, but, except for coincidences, there is no curvilinear relationship between *S*_{wt} and *n* except within the same bed, and the bed exhibits uniform distributions of oil, water, porosity, and other factors influencing electrical conductivity, as the individual curves in Figure 10 illustrate.

**What if the imaginary values are used in interpretation?** Slope *m* in **Figure 1** is a resistivity gradient representing the value of *R*_{0} at 100% electrical efficiency in the selected rock at all porosities. If slope *n* were to lie below slope *m *, resistivity *R*_{t} would lie below the extrapolated values of *R*_{0} , and oil saturations would be artificially overestimated over all porosities and saturations. This is a commonplace occurrence in literature that has become a factoid of conventional wisdom. The presence of oil cannot increase the electrical conductivity of water more than 100% efficiency (*m*). See **Figure 6** and **APPENDIX (D)**.

**Figure 9**. Description of Well 3. This well log, too, is a vintage resistivity log. This log was chosen because of its simplicity. In this figure is a resistivity log in a water-wet rock. Like the two examples above, the resistivity curves show great contrast between an oil-bearing zone and a water-bearing zone. This example shows a dual induction log with an SP curve. At the top of the bed between X151 and X161 is an oil-bearing interval marked Zone A. Near the bottom of the bed is a water-bearing interval between X183 and X192 marked Zone B.

The calculated values of *n* relative to water saturations for this bed also are shown as a curve in **Figure 10**.

A moderately high value of saturation exponent *n* up to perhaps 8 or 9 might not be a factor in distinguishing between water-wet and oil-wet rocks.

As it can be seen in Figure 10, as water saturation in Well 3 increases, the calculated curve for *n* will increase again the same as the curves for Wells 1 and 2. This, again, is corroborated by the slope CG representing exponent of triangle CDG in the model in **Figure 1**.

Examine the effectiveness curve from Zone A of Well 3 in **Figure 10**. This curve is plotted from values of exponent *n* in water-wet rock. It can be seen that the curve is very similar to the curves from oil-wet rock. Why is this so?

It is a simple matter for a computer to solve the necessary equations and iterations required to compute the results appearing in Figure 10. Let’s examine how exponent *n* is calculated:

In the calculation of each exponent *n*, *R*_{w} first must be calculated from Equation(1b) for each iterated value of *S*_{wt} . Along with *R*_{we} , exponent *n* must be solved from triangle CDG in Figure 1 or from the dual-water Archie equation, Eq.(4b):

* S*_{wt}^{n} = (1.0 / ( * ϕ_{t}^{m}*1

where from triangle CDG of Figure 1,

*n* = ( log*R*_{t} - log*R*_{0} ) / ( log1 - log*S*_{wt} ) = ( log*R*_{0} - log*R*_{t} ) / ( log*S*_{wt} )

It can be seen in Eq.(4b) above, that the ratio ( *R*_{0} / *R*_{t measured}_{ }) varies little for each Zone A in the Wells 1, 2, and 3. Therefore, the equation for each curve in Figure 10 is:

*S*_{wt}^{n} = A near constant for each depth of interest depending on the value of the ratio.

Solve for *n* by iterating *S*_{wt} in Eqs.(1b) and (4b).

**Can oil-wet zones be distinguished from water-wet zones by high values of n?** Sometimes and sometimes not. In Well 1, Zone A, an oil-wet zone, the ratio of (

In some oil-wet rocks, the ratio might be very small. The ratio of *R*_{0} / *R*_{t measured} might be 10/1,000 or 10/10,000. It can be seen in Equation(4b) that as *R*_{t} inceases (or *R*_{we} decreases), exponent *n* increases. The ratio *R*_{0} / *R*_{t} in this order of magnitude moves the type curve shapes upward in **Figure 10** because exponent *n* increases everywhere. As *R*_{t} increases, point H on both Figure 1 and Figure 10 will be shifted to the right toward higher calculated maximum oil saturations.

The values for exponent *n* are viable only at higher oil saturations than irreducible oil saturations. This must be taken into consideration. The calculated bulk volume of oil consists of producible oil and irreducible oil; and the calculated bulk volume of water consists of water that can be produced, irreducible water, and water, or pseudo water, contained in dynamically non-effective rock constituents.

**What about the steep upward sweep of n at high water saturations?** Like the values of

The actual values of *n* must gradually return to the value of *m* at high water saturations so that at 100% water saturation and 0% oil saturation exponent *n* becomes *m* again. From some location on the effectiveness curve, as water saturation increases, the value of *n* will increase to a maximum whereupon, as water saturation continues to increase, *the value of n* declines followed by a decline of *R _{t}* until the water saturation becomes 100%,

The dashed curve in Figure 10 is one of a number of artful conceptions that exponent *n* might take as oil migrates into or out of water-wet- or oil-wet rock, simultaneously changing *R*_{t} . As *R*_{t }increases, the ratio *R*_{0} / *R*_{t} (in Eq.(4b)) decreases and exponent *n* increases. As *n* increases, the apex becomes narrower and sharper from which *n* declines to approach and ultimately return to exponent *m* at 100% water saturation.

In Figure 10, the effectiveness curves under these conditions might resemble normal frequency curves skewed heavily toward high water saturations, and slope CG in triangle CDG in Figure 1 might correspondingly morph into a shape similar to a lazy S as high water saturations approach 100%.

Both the model in Figure 1 and the curves in Figure 10 would be modified as *R*_{t} changes to correspond with the reasoning set forth above.

**What about exponent m_{2}?** This is a single saturation exponent equivalent to the two exponents

Everything that has been said about exponent *n* applies to exponent *m*_{2} with the exception that the effects on or by *m*_{2} will be smaller. On both Figure 1 and Figure 10, where the slope of exponent *n* meets the slope of *m* at point H, so does the slope of exponent *m*_{2} meet slope *m* at point H.

**A CLARIFYING CONCEPT OF ARCHIE'S RESISTIVITY RELATIONSHIPS AND PARAMETERS.**

**A MODEL AND DISCUSSION**

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