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A Petrophysical Method to Evaluate Irregularly Gas Saturated Tight Sands Which Have Variable Matrix Properties and Uncertain Previous HitWaterNext Hit Salinities*

 

Michael Holmes1, Dominic Holmes1, and Antony Holmes1

 

Search and Discovery Article #40673 (2011)

Posted January 11, 2011

 

*Adapted from oral presentation at AAPG International Conference and Exhibition, Calgary, Alberta, Canada, September 12-15, 2010

 

1Digital Formation, Denver, Colorado ([email protected])

 

Abstract

 

A problem in many Rocky Mountain tight gas sandstones is a sequence that is only partially gas saturated, with changing matrix properties combined with variable (and often unpredictable) Previous HitwaterNext Hit salinities. Often it is difficult to distinguish between high resistivity fresh Previous HitwaterNext Hit wet sands, and high resistivity, gas-bearing sands. A standard approach is to make a qualitative judgment based on density/neutron response – the gas “cross-over” effect. However, if matrix properties are variable, this approach can be misleading, and is at best a qualitative judgment.

 

The methodology presented here is a quantitative assessment of gas saturation by comparing matrix specific density and neutron responses with porosity, calculated such that gas effects are minimized. Cross plot porosity from density/neutron combination is only minimally affected by gas and by changing matrix properties.

 

Three sets of calculations are made assuming sandstone (bulk density 2.65 gm/cc), calcareous sandstone (bulk density 2.68 gm/cc) and heavily cemented calcareous sandstone, or limestone (bulk density 2.71 gm/cc). Quantified estimates of gas saturation, as “seen” by each log, are available for each assumed rock type. Pressure effects on porosity log responses are included in the calculations.

 

Four sets of saturation profiles are now available, one from standard resistivity log analysis and three from porosity log analysis assuming different matrix properties. Comparisons among the 4 sets of saturation profiles can be combined with other data, such as mud log shows and (if available) core measured matrix densities. Using such comparisons, it is often relatively simple to distinguish between wet intervals and gas-bearing intervals. With increasing assumed grain density, gas saturations calculated from the porosity logs increase. If gas saturations so defined are unrealistically high, it is an indication that actual grain density is less than assumed grain density.

 

Additionally, if matrix properties are well-defined, it is possible to verify Rw input for resistivity log interpretation, and adjust as necessary. It is important to recognize that the porosity logs, and particularly the density log, investigate close to the wellbore, and may well be influenced entirely by the flushed zone. Examples are presented from Rocky Mountain reservoirs, in sequences where the problem of irregular gas saturation in systems with variable Rw is particularly severe.

 

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Copyright � AAPG. Serial rights given by author. For all other rights contact author directly.

 

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fig01

Figure 1. Schematic of gas saturation from porosity log analysis (for shallow reservoirs).

fig02

Figure 2. Depth log from standard shaley formation resistivity analysis. Track descriptions are as follows: (1) raw wireline log; (2) reservoir composition, where yellow indicates matrix, red indicates porosity, and grey indicates shale; (3) Previous HitwaterNext Hit saturation, core data illustrated by blue and green symbols; (4) bulk volumes where grey indicates shale, brown indicates hydrocarbons, light blue indicates poor quality reservoir (possible mobile Previous HitwaterNext Hit), and dark blue indicates capillary Previous HitboundNext Hit Previous HitwaterNext Hit; (5) pay flags where yellow indicates gross reservoir, red indicates net reservoir, and green indicates net pay.

fig03

Figure 3. Interpretation of porosity vs. resistivity relations to determine parameters for Archie analysis. a (cementation constant) = 1.0, Rw (Previous HitwaterNext Hit resistivity) = 0.1, m (cementation exponent) = 2, and n (saturation exponent) = 1.7.

fig04

Figure 4. Depth log showing gas saturation from porosity log analysis. Track descriptions are as follows: (1) reservoir composition, where yellow indicates matrix, red indicates porosity, and grey indicates shale; (2) Previous HitwaterNext Hit saturation, core data illustrated by blue and green symbols; (3) bulk volumes, where grey indicates shale, brown indicates hydrocarbons, light blue indicates poor quality reservoir (possible mobile Previous HitwaterNext Hit), and dark blue indicates capillary Previous HitboundNext Hit Previous HitwaterNext Hit; (4) matrix properties - grain density and matrix travel time; (5) permeability, core data illustrated by black symbols. Tracks 6, 7, and 8 show porosity and gas saturation from porosity logs only. Yellow indicates gas saturation from porosity logs, and blue indicates Previous HitwaterNext Hit saturation from resistivity log analysis. Track 6 shows analysis assuming a grain density of 2.65 gm/cc, track 7 shows analysis assuming 2.68 gm/cc, and track 8 shows analysis assuming a grain density of 2.71 gm/cc. Track 9 contains pay flags where yellow indicates gross reservoir, red indicates net reservoir, and green indicates net pay. 9a shows pay flags from resistivity analysis, 9b shows pay flags from porosity log analysis assuming grain density of 2.65 gm/cc, 9c shows pay flags from porosity log analysis assuming grain density of 2.68 gm/cc, and 9d shows pay flags from porosity log analysis assuming grain density of 2.71 gm/cc.

 

Methodology

 

Shaley Formation Resistivity Analysis

 

The interpretation is a standard shaley formation analysis, involving calculations of total porosity, shale volume, and total Previous HitwaterNext Hit saturation. One of the issues in tight gas sands is the correct choice of matrix lithology. If only a density log is used, the correct choice of grain density is crucial. In the event of lack of core data this may be particularly problematic, especially if grain density is variable. By using a density/neutron cross plot, this restriction is overcome. Fluid density is a required input, and should be estimated from a reasonable assumption of gas saturation close to the wellbore. A porosity/resistivity cross plot can help in this choice.

 

The second set of analysis involves the calculation of effective porosity and Previous HitwaterNext Hit saturation (i.e. removing the effects of clay). From these calculations, again based on resistivity interpretations, potential mobile Previous HitwaterNext Hit and/or poor quality reservoir rock can be distinguished from capillary Previous HitboundNext Hit Previous HitwaterNext Hit. Lack of light blue color fill on Figure 2, track 4 and Figure 4, track 3 equates to better quality, gas-bearing reservoirs. Example of application of these techniques are described in AAPG Annual Convention, June 2009 “Relationship Between Porosity and Previous HitWaterNext Hit Saturation: Methodology to Distinguish Mobile from Capillary Previous HitBoundNext Hit Previous HitWaterNext Hit ” by Michael Holmes, Antony Holmes, Dominic Holmes.

 

Gas Saturation from Porosity Logs

 

Comparison of density with neutron logs is used routinely for a qualitative assessment of the presence of gas – the density/neutron “cross-over” effect. The response is controlled by the concentration of hydrogen in the pore space. Because gas contains less hydrogen than oil or Previous HitwaterNext Hit, apparent neutron porosity is suppressed. The cross plot (Figure 1) shows the effects of gas. Porosity values are lithology specific, i.e. raw logging data must be converted to a known (or presumed) lithology. By assuming different lithologies, the cross plot can be solved for gas saturation. The assumption is made that the density and neutron logs both investigate about the same volume of rock – or, as in the case of tight gas sands, there is a little variation of gas saturation away from the wellbore (minimal or no invasion by drilling fluid). Three different lithologies are assumed in this paper:

 

 

 

Example

 

Standard resistivity interpretation from a Piceance Basin well, NW Colorado, is shown in Figure 2. Interpretation of the porosity resistivity cross plot (Figure 3) shows input used for saturation determination:

 

Rw = 0.1 Previous HitWaterNext Hit resistivity

a = 1.0 Cementation constant

m = 2.0 Cementation exponent

n = 1.7 Saturation exponent

 

A summary of the interpretation is as follows:

  • Sands from 4850-5000 ft are either tight (as at 4890-4910 ft) or wet (as at 4920-4940 ft).
  • From 5000-5140 ft the sands are routinely gas bearing and, for tight sands, fair reservoir quality – average core permeability 0.1 mD or above.
  • From 5140-5200 ft, the sands are tight – average core permeability less than 0.01 mD.

 

Figure 4 shows the same interval as Figure 2, with the addition of interpretations of gas saturation from porosity logs. Examination of the porosity log Sg data shows the following:

  • None of the sands has a grain density of 2.71 gm/cc (calculations assuming this value show unrealistically high gas saturations).
  • The shallower sands (above 5000 ft) appear to be mostly wet, with a grain density of 2.65 gm/cc - or they are gas bearing with a more saline Previous HitwaterTop (lower Rw) than the shallower sands, with a grain density of 2.68. Core measured grain densities would help solve the problem.
  • Sands from 5000-5140 ft are gas bearing with a grain density of 2.68 gm/cc.
  • Sands below 5140 ft are not gas bearing, regardless of assumed grain density.

 

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