Chapter 4

Chapter 4Reservoir Parameters for Shaly Sand Reservoir: A Case Study

The case study is based on the interpretation of well log data for a shaly sand reservoir

from a particular field of Eastern offshore basin, India. Available data is in three different

tracks. Track 1 includes caliper and gamma logs in meters and API units respectively. Track

2 includes resistivity data both LLD and LLS in ohm-m respectively. Track 3 includes two

porosity logs namely Neutron Log and Density log in gm/cc. Well Log record is shown in

Annexure.

The data has been interpreted manually and by using excel for reservoir parameters

estimation of this particular field. Data from well log data have been digitized at 0.1524

meter interval.

Fig 4.1 Layout preparation for different Log types

4.1. Identifying the Reservoir

For this particular log data the reservoir zones of interest have been identified by

using the combination of all available logs. The most reliable indicator of reservoir rock will

be from the behavior of the density/neutron logs, with the density moving to the left (low

density) and touching or crossing the neutron curve. In clastic reservoirs in nearly all cases

this will correspond to a fall in the gamma ray (GR) log. In a few reservoirs, the GR is not a

reliable indicator of sand, due to the presence in sands of radioactive minerals.

Shales can be clearly identified as zones where the density lies to the right of the neutron.

The greater the crossover between the density and neutron logs, the better the quality of the

reservoir.

4.2. Identifying the fluid type and contacts:

If regional information is available regarding the positions of any gas/oil contact (GOC)

or oil/water contact (OWC), then convert these subsea depths in to measured depths in the

current well and mark them on the logs.

If the formation pressures have already been measured, then any information on possible free

water levels (FWLs) or GOCs can also be marked on the log.

Start by comparing the density and deepest reading resistivity log for any evidence of

hydrocarbons. In the classic response the resistivity and density (and also GR) will be seen to

follow each other to the left or right in water sands and to be a mirror image of each other in

hydrocarbon sands. However, some hydrocarbon/water zones will not exhibit such behavior,

the reasons being:

When the formation-water salinity is very high, the resistivity may also drop in clean

sands.

In shaly sand zones having a high proportion of conductive dispersed shales, the

resistivity may also fail to rise in reservoir zones.

If the sands are thinly laminated between shales then also resistivity may remain low.

For this particular log data the reservoir zones of interest have been identified by using the

combination of all available logs. As stated earlier gas zones will exhibit a greater

density/neutron crossover than oil zones. In very clean porous sands any GOC can be

identified on the log relatively easily.

I have proposed here so many ways like crossplots, shale baseline shifts to identify gas zones,

oil and water bearing zones and their contacts in a reliable manner. I have interpreted the

given depth of interval comprising three different fluids of gas, oil and water. From the above

I have made the zonation depending on fluid type.

Reservoir extends from a depth of 4220.06 m to 4309.976 m that is almost 90 meter

thick reservoir. This 90 meter thick reservoir consist of several packets of potential zones and

others very thin reservoir units. Potential zones include:

Zone 1: 4220.06 - 4264.71

Zone 2: 4264.71 - 4289.70

Zone 3: 4289.70 - 4309.97

These all zones have been interpretated for their reservoir parameters estimation.

Fig 4.2 Hydrocarbon Zone identification

Fig 4.3 Zonation based on N-D Cross plot data and pressure plot data

4.3. Parameters Estimation

All the parameters have been estimated for the given well log data.

4.3.1. Formation Water Resistivity Estimation

The following two methods have been used in order to estimate the formation water

resistivity. These include:

Archie’s Equation

Pickett Plot

For Archie’s equation a zone which seems to be clean, having low resistivity and 100

percent saturated with water have been selected. Formation water resistivity has been found

to be 0.09 ohm-m. For further interpretation a value of 0.09 ohm-m was chosen for

formation water resistivity.

4.3.3. Volume of shale Estimation

Volume of shale for this particular case has been estimated by using two methods.

They are Gamma method and Neutron-Density method.

From gamma ray log

Vsh_GR = (GR-GRmin ) / (GRmax - GRmin )

GR = Gamma ray log reading

GRmin = Gamma ray log reading in 100% clean zone

GRmax = Gamma ray log reading 100% shale

All readings are API units

Vsh from Neutron – Density:

Vsh_ND = (fN-fD) / (fN_sh-fD_sh)

Where Vsh_ND = volume of shale

fD = Porosity from Density

fN = Neutron porosity

fD_sh = Shale density

fN_sh = Shale Neutron porosity

Vsh from N-D: (In Gas bearing zones)

Vsh_ND = (fD-fN(fD/fN)max) / (fD_sh-fN_sh(fD/fN)max)

Where

Vsh_ND = volume of shale

fD = Porosity from Density

fN = Neutron porosity

(fD/fN)max = Maximum ratio from interested zone

The limits are under the tolerance limit so one may consider the zones as relatively clean

with minor amount of shaly component present in the zones of interest.

4.3.4. Effective Porosity Estimation

In order to calculate formation water resistivity and water saturation, there requires only

one porosity that is effective porosity. Porosity estimated should be corrected for volume of

shale and compaction. After correcting the porosities they should be plotted on cross plot

charts and an estimate of effective porosity can be done. The other method uses mathematical

equation for estimating effective porosities.

Effective Porosity Estimation:

fe = ft – Vsh_min*ft_sh

fe = effective porosity

ft = total porosity

ft_sh = total porosity of shale

Vsh_min = minimum of shale volume calculated from logs (GR, N-D etc.)

(0.3*PHIN+0.7PHID) for gas bearing zones

(PHIN+PHID)/2 for water or oil bearing zones

Zone-1 Zone-2

Zone-3

Fig 4.4 Shale volume and Porosity estimation for all three zones

4.3.5. Water Saturation Estimation

The ultimate aim of any log interpretation is to estimate the water saturation. As far as

shaly sand types of reservoirs are concerned, various equations and models have been

proposed for estimating the water saturation. The most common and widely used are Archie’s

equation, Indonesian Equation and Dual water model. Archie’s equation has been used for

estimating water saturation for the zones of the interest.

Generalized Archie’s equation is:

Here

Here, Φ denotes the porosity,

Sw is the brine saturation,

m is the cementation exponent of the rock (usually in the range 1.8–2.0),

n is the saturation exponent (usually close to 2) and

a is the tortuosity factor.

4.3.6. Petrophysical Cut-offs:

Effective porosity ≥ 0.06

Water Saturation ≤ 0.85

Volume of Shale ≤ 0.9

4.3.6 Gross to Net calculation:

Pay: Thickness of productive reservoir

Gross Pay: Total vertical interval of productive zone

Net Pay: Thickness of actual productive intervals, excluding intervening non productive

layers.

Fig 4.5 Difference b/n Net pay and Gross pay

4.4. Results and Discussions

The results obtained after detailed interpretation for all zones of interest can be

summarized as:

Formation Water Resistivity (Rw) 0.09 ohm-meters

Lithology Clean Sand, shaly sand with some

intercalations of calcite steaks

Average Vsh

Average Phie

Average Swe

Fluid Type Major Gas, minor Oil, and a water zone.

Hydrocarbon Pore Thickness

Gross Pay

Net Pay Zone 1:

Zone 2:

Zone 3:

For the given well all the reservoir parameters has been estimated manually. Based on

these estimated values of parameters, well can be considered as potentially viable for

production having hydrocarbon saturation about 31-88%. However there are certain points

which have to be discussed in order to interpret the well correctly.

Volume of shale for all zones of interest has been calculated by using all available

methods and a lower value has been chosen.

One of the most important parameter for characterizing a reservoir is its effective

porosity. A reservoir in order to be called potentially viable should have good values of

effective porosity. But the porosities derived from these logs have effect of presence of shale,

compaction and others. So they should be corrected in order to estimate effective porosity.

Density and neutron porosities have been corrected for volume of shale. Cross plots and

mathematical formulas have been used for estimating effective porosities for all zones.

The ultimate aim of any log interpretation is to estimate its water saturation. Various

methods have been used for estimating water saturation for this well. Which method will give

right value depend on a number of parameters. These include type of shale present in the

reservoir, lithology and available data. For zones having a shale volume less than 9%

Archie’s saturation equation have been used for estimating water saturation.

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