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Log analyses in tight gas reservoirs
Logs provide the most economical and complete source of data for evaluating layered, complex, low porosity, tight gas reservoirs. The recommended logging suite for a tight gas reservoir consist of:
- Spontaneous potential (SP)
- Gamma ray (GR)
- Density (FDC)
- Neutron (CNL)
- Sonic (SON)
- Dual (or array) induction logs (DIL)
Preprocessing data
All openhole logging data should be preprocessed before the data are used in any detailed computations. The steps required to preprocess the logs are:
- Digitize all log data
- Depth shift the data as required
- Perform all environmental corrections
- Normalize data so that all logs from different wells are reading the same in zones, such as thick marine shales in which one expects the log readings to be consistent from well to well.^{[1]}^{[2]}
Once the data have been preprocessed and stored in a digital database, a series of statistical analyses must be conducted to quantify certain evaluation parameters. These statistical analyses consist of a Picket plot to determine estimates of:
- Water resistivity (R_{w}), cementation factor (m), and saturation exponent (n)
- Shale histograms to find the shale endpoints on all logs
- Sand and/or limestone histograms to determine the clean zone endpoints on all the logs
- Linear regressions between each porosity log and any core data to establish correlation constants
- Linear regressions among the porosity logs to develop correlations that can be used to correct for bad hole effects on one or more of the logs
The series of articles by Hunt et al.^{[3]} clearly describes the steps required to:
- Preprocess the logs
- Develop the correlation parameters
- Analyze logs in shaly, low porosity formations
Computing porosity
To correctly compute porosity in tight, shaly (clay-rich) reservoirs, one of the first values to compute is the volume of clay in the rock. The clay volume is normally computed using either the self-potential (SP) or the GR log readings. The following equations are commonly used to compute the clay volume in a formation.
The SP provides reasonable estimates of V_{SH} if the formation water and the mud filtrate do not have the same salinities. The GR log provides reasonable estimates of V_{SH} as long as all the radioactive materials in the formation are part of the clays and not part of the sandstone, such as potassium feldspar.
Once the values of V_{SH} are known as a function of depth, then the petrophysicist can compute values of clay-corrected porosity from the density, neutron, and sonic logs with Eqs. 5, 6, or 7.
If the petrophysicist only has a density, sonic, or neutron log, the clay-corrected estimates of porosity from Eqs. 5, 6, or 7 should be used to determine the porosity. However, if two or all three logs are available, crossplots should be used to determine the best estimate of porosity.^{[3]}
Computing water saturation
There have been numerous water saturation equations published in the petroleum engineering and petrophysical literature. Worthington^{[4]} published a complete review of all the commonly used water-saturation equations. For tight gas sandstones, the best method to compute the value of water saturation is normally the dual-water model.^{[5]} Eq. 8 and Fig. 1 illustrate the dual-water model.
and
It is possible to use a clay-corrected Archie equation, the Simandeaux equation, the Waxman-Smits equation, or any number of other equations as described by Worthington;^{[4]} however, for many situations, the dual-water model provides accurate estimates of water saturation.
In the Archie equation, all the electrical conductivity in the formation is assumed to be transmitted through the water in the pore space. The rock is assumed to be an insulator and does not conduct current. However, in clay-rich formations, the clays conduct an electric current. The Simandeaux and Waxman-Smits equations provide for a conductive rock but assume that the water associated with the pore space and the water associated with the clays have the same properties. In the dual-water model, there is free water and bound water. The free water is in the pores, and the bound water is associated with the clays. More accurate estimates of water saturation can be achieved by taking into account the current conducted by the clays using the dual-water model.
When the formation permeability in a gas reservoir is between 0.01 and 10 md, mud filtrate invasion from freshwater mud into a formation with saline interstitial water can substantially alter the resistivity profile near the wellbore during the time period before the openhole logs are normally run.^{[6]} In such cases, dual-induction logs or array-induction logs should be run and used to make corrections to determine the true resistivity, R_{t}, of the formation. The log readings change with time because of mud filtrate invasion.
Most tight gas reservoirs are tight because they are highly cemented and have low porosity. The low porosity and cementation cause many tight gas reservoirs to become hard and abrasive, which may prevent the use of logging while drilling (LWD) equipment. In addition, the flow rates and ultimate recovery from individual wells are low, and the operator must control drilling, completion, and operating costs to improve the profitability of each well. For these reasons, LWD is not often used when drilling tight gas reservoirs. Most of the logging data come from openhole logs run after the well reaches total depth. See more discussion on logging practices in the section on petrophysics in Geothermal reservoir engineering
Mud filtrate invasion
In many tight gas formations, drilling mud mixed with fresh water is used to drill. Commonly, the formation water is more saline than the water in the drilling mud. When the drill bit penetrates a permeable formation, filtrate from the drilling mud invades the formation.^{[7]} The factors that affect mud filtrate invasion are:
- Mud cake properties
- Reservoir pressure
- Mud weight
- Formation permeability
- Formation porosity
- Relative permeability
- Capillary pressure
The factors that affect the resistivity profile around the well, in addition to the above factors, are:
- The formation water salinity
- The mud filtrate salinity
- The initial water saturation in the formation
In low permeability gas reservoirs, mud filtrate invasion during drilling can affect the results from both drillstem tests and from openhole logs.^{[8]}^{[9]} The mud filtrate invades the permeable zones, and the mud filtrate invasion profile changes with time. Therefore, the values recorded by logging tools are a function of when those logs are run. In addition, values such as mud weight, mud filtrate salinity, and mud circulation rate can change hourly or daily. As such, it is important to measure the mud properties daily and to keep accurate records during drilling operations.
The fact that mud filtrate invasion in low porosity rocks does affect openhole logs can be used to the advantage of the log analyst. Semmelbeck et al.^{[6]} explained how mud filtrate invasion in low permeability formations affect the deep induction (R_{ild}) and the medium induction log (R_{ilm}) differently as a function of time. Thus, if one has multiple logging runs, one can evaluate how the ratio of R_{ild} /R_{ilm} varies and can correlate that ratio with formation permeability. Fig. 2 shows simulated data that describes how the ratio of R_{ild} /R_{ilm} for one set of reservoir and drilling mud parameters varies over time as a function of reservoir permeability. Notice that the resistivity ratio changes with time as the mud filtrate continues to invade the formation. It is clear that the mud filtrate invasion affects the different resistivity logs more in high permeability formations than in low permeability formations. As such, evidence of mud filtrate invasion from log analyses can be used to estimate values of formation permeability.^{[6]}^{[9]}^{[10]}
The SFE No. 3, a GRI research well in East Texas, was logged four times while drilling to measure the effects of mud filtrate invasion on the readings from openhole logs.^{[11]} Fig. 3 presents some of the data for a portion of the hole in SFE No. 3. Because the resistivity measurements are changing with every logging run, it is clear that mud filtrate invasion affects the openhole resistivity logging readings in the permeable zones. However, in the shales, where minimal invasion occurred, the effects of invasion are minimal as the resistivity readings do not vary between logging runs. As a rule of thumb, if the analyst sees evidence of mud filtrate invasion on the resistivity logs and/or mud cake across a gas-bearing zone, then that zone should have enough permeability to produce gas at measurable flow rates.
Mud filtrate invasion also affects the sonic velocities, the bulk densities, and the hydrogen content of the portion of the rock near the wellbore that is invaded. As such, mud filtrate invasion also affects the sonic, density, and neutron log readings. As mud filtrate invasion proceeds, the properties change with time, and the readings from the sonic, density and neutron logs will also change with time.^{[11]}
Nomenclature
A | = | surface area |
C | = | conductivity, mho/m |
I | = | index |
ρ | = | density, g/mL |
t | = | time, hours or days |
Δt | = | travel time, μsec/ft |
V | = | volume, fraction |
φ | = | porosity, fraction |
Subscripts
b | = | bulk |
CL | = | clean |
f | = | fluid or fracture |
ma | = | matrix |
N | = | neutron log |
NC | = | neutron corrected for shale |
RA | = | radioactive |
SC | = | sonic corrected |
SH | = | shale |
t | = | true (for conductivity); total (for compressibility) |
w | = | wellbore (for radius); water (for saturation) |
wb | = | bound water (for conductivity and water saturation) |
wf | = | well flowing; free water (for conductivity) |
wt | = | total water |
Superscripts
m | = | cementation factor |
n | = | saturation exponent |
References
- ↑ Aly, A.M., Hunt, E.R., Pursell, D.A. et al. 1997. Application of Multi-Well Normalization of Open Hole Logs in Integrated Reservoir Studies. Presented at the SPE Western Regional Meeting, Long Beach, California, 25-27 June 1997. SPE-38263-MS. http://dx.doi.org/10.2118/38263-MS.
- ↑ Howard, W.E. and Hunt, E.R. 1986. Travis Peak: An Integrated Approach to Formation Evaluation. Presented at the SPE Unconventional Gas Technology Symposium, Louisville, Kentucky, 18-21 May 1986. SPE-15208-MS. http://dx.doi.org/10.2118/15208-MS.
- ↑ ^{3.0} ^{3.1} Hunt, E.R. et al. 1997. Fundamentals of Log Analysis. 12-part article in World Oil (June, July, September, October, November, December 1996 and March, July, September, October, November, December 1997).
- ↑ ^{4.0} ^{4.1} Worthington, P.F. 1985. The Evolution of Shaly-Sand Concepts in Reservoir Evaluation. The Log Analyst (January/February): 23.
- ↑ Clavier, C., Coates, G., and Dumanoir, J. 1984. Theoretical and Experimental Bases for the Dual-Water Model for Interpretation of Shaly Sands. SPE J. 24 (2): 153-168. SPE-6859-PA. http://dx.doi.org/10.2118/6859-PA.
- ↑ ^{6.0} ^{6.1} ^{6.2} Semmelbeck, M.E. and Holditch, S.A. 1988. The Effects of Mud-Filtrate Invasion on the Interpretation of Induction Logs. SPE Form Eval 3 (2): 386-392. SPE-14491-PA. http://dx.doi.org/10.2118/14491-PA.
- ↑ Ferguson, C.K. and Klotz, J.A. 1954. Filtration from Mud During Drilling. J Pet Technol 6 (2): 30–43. SPE-289-G. http://dx.doi.org/10.2118/289-G.
- ↑ Holditch, S.A., Lee, W.J., Lancaster, D.E. et al. 1983. Effect of Mud Filtrate Invasion on Apparent Productivity in Drillstem Tests in Low-Permeability Gas Formations. J Pet Technol 35 (2): 299-305. SPE-9842-PA. http://dx.doi.org/10.2118/9842-PA.
- ↑ ^{9.0} ^{9.1} Tobola, D.P. and Holditch, S.A. 1991. Determination, of Reservoir Permeability From Repeated Induction Logging. SPE Form Eval 6 (1): 20-26. SPE-19606-PA. http://dx.doi.org/10.2118/19606-PA.
- ↑ Yao, C.Y. and Holditch, S.A. 1996. Reservoir Permeability Estimation From Time-lapse Log Data. SPE Form Eval 11 (1): 69–74. SPE-25513-PA. http://dx.doi.org/10.2118/25513-PA.
- ↑ ^{11.0} ^{11.1} Staged Field Experiment No. 3: Application of Advanced Technologies in Tight Gas Sandstones—Travis Peak and Cotton Valley Formations, Waskom Field, Harrison County, Texas. Gas Research Inst. Report, GRI-91/0048, CER Corp. and S.A. Holditch & Assocs. Inc. (February).
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See also
Log analysis in shaly formations
Core analyses in tight gas reservoirs
Permeability estimation in tight gas reservoirs
Tight gas drilling and completion
Statistical data correlations in tight gas reservoirs
Reserves estimation in tight gas reservoirs
Hydraulic fracturing in tight gas reservoirs