# Helpfile for VOLCALC

### General

Volcalc is a program to calculate reserves in a single reservoir on the basis of a number of reservoir and PVT variables. It gives the results as the conditional or "Unrisked" volumes. For a complete appraisal of an exploration opportunity, an estimate of the geological probability of success ("POSg") will be required. This is usually done by estimating a number of necessary ingredients of the Petroleum System, notably the probabilities of fulfillment of HC charge, Trap, Reservoir, Seal, and Retention. Those subjective probabilities are then multiplied to obtain the POSg.

### Input variables

The input/output options for units are "Metric" or "Oil Field Units", (OFU).
There are five input sheets:

1. The Metric main input form.
2. The OFU main input form
3. The Metric Trap input
4. The OFU Trap input
5. The Geological POS input (POSg)

In addition, there are (and explained further down):

1. Number of Monte Carlo cycles input box If left blank the standard 10,000 cycles are used in the Monte Carlo analysis.
2. Appraisal model: There are four options to choose from.
3. Lithology of reservoir for deault porosity estimation.
4. Trap model

The application of economic cutoff volumes for oil and gas will usually produce a volume expectation curve that includes zero volumes, even given a geological POS of 100%. The zeros produced in the simulation are the small volumes that are less than the cutoff. So if we have a POSg (geological, not taking economics into account) and a "conditional" POSv (the POS of the volume alone and also called "unrisked volume") , the total POSc becomes POSc = POSg * POSv (the product of POSg and POSv as fractions).

### The probability of Success (POS).

The POSg facility allows the user to estimate probabilities of fulfillment for the elements of the petroleum system subjectively. The main factors considered are:

1. Hydrocarbon charge
2. Trap
3. Timing
4. Reservoir
5. Seal

The product of these probabilities (as fractions instead of the input percent) is the POSg. It is assumed that these probabilities are fully independent. That a factor such as "recovery" is not included is because we feel that this is an economic factor, although it can be predicted by geological variables, such as reservoir and oil quality. Hence the POSg is effectively a subjective chance to find "Oil in place" (c.q. Gas , Condensate). A further refinement is to add the conditional chance of having Free Gas, given hydrocarbons P[FG|HC] and the conditional chance of having Condensate, given Free Gas: P[Cond|FG].  The above figure gives the upper part of the input window.
Metric input is the default, but a similar window for Oil Fields Units ("OFU") is provided under the menu item Options.

• Depth, in M
This parameter is required for the calculation of the PVT conditions.
It also is required for the HC contact appraisal option.
• Waterdepth in M
Required to estimate the reservoir temperature, with the depth and temperature gradient.
• Area at spillpoint in Km2
Optional. Will be calculated from Length and Width, if required.
• Length of trap at spillpoint, Km
required if Area not given.
• Width of trap at spillpoint, Km, Required if area not given. Obviously, either Area or Length/Width have to be provided.
• Vertical closure in M
From the culmination down to the geometrical spillpoint, or in the case of a faulttrap, down to the lateral leakpoint.
• Gross reservoir thickness in M
• Net to gross ratio, input %
• Porosity, %. If not given, a world-wide default distribution is inserted, based on the depth. For this purpose a choice can be made between siliciclastic and carbonate reservoirs, as the default distributions and regression versus depth differ. The choice is made in a box in the right upper corner of the input window.
• Hydrocarbon saturation, %
The complement of the water saturation.
• Expansion factor (gas)
It will be calculated by the program from other input variables. This involves the depth/pressure, gas density, reservoir temperature and a routine to estimate the z-factor for non-ideal gas.
• Formation Volume Factor (oil), also called shrinkage factor
It will be calculated by the program from other input variables.
• Surface Temperature, C.
This should be water bottom temperature if waterdepth > 0 m
• Temperature gradient Deg. C/100 M
If not given, a world-wide default distribution is inserted.
• Reservoir Temperature, degrees C.
If not given, it is calculated from depth, waterdepth and gradient.
• Reservoir Pressure in Bar
This is estimated from the depth below surface. The in put would be required in the case of overpressured reservoirs.
• Oil density in Kg/M3
If not given, a world-wide default distribution is inserted.
• Gas density (air=1)
If not given, a world-wide default distribution is inserted.
• Gas/Oil ratio (v/v)
If not given, it is calculated by the program from other inputs.
• Condensate ratio (M3/Million M3)
If not given, a world-wide prior is used.
• Non-HC gas, % If not given a zero content is assumed.
• --------------- Column appraisal
• HC column in M
• Gas Column as % of HC column
• ---------------- Contact appraisal
• Depth of OWC in M
• Depth of GOC in M
• ----------------
• Recovery eff. %, Oil
If left blank, a world-wide default distribution is provided
• Recovery eff. %, Gas
If left blank, a world-wide default distribution is provided
• Recovery eff. %, Condensate

The condensate recovery is a two-step calculation: First gas has to be recovered, then only a fraction of the condensate in the produced gas may be recovered.

• Cutoff for Oil
Economic minimum that applies to recoverable oil.
• Cutoff for Gas
Economic minimum that applies to recoverable gas. Note that the condensate production is only realized if the recoverable gas is larger than cutoff. Therefore the gas cutoff determines the condensate minimum, but this has no economic meaning.

Distribution type. Five distribution types are available as listed below in more detail. For the relevant input column, click with the right button on the input cell and click on the desired distribution type in the popup menu to make sure the correct distribution code is entered.
Each variable can be have a "low" (L), a "middle" (M) and a "high" (H) value as input. These may all be equal, or in increasing order, not otherwise. In the second column of the input grid the distribution type can be specified as follows:

1. Constant ("C")
The first entry is used and a vector with this constant is created
2. Rectangular ("R")
The first and last number, i.e. the Low and the High are used as the boundaries of a uniform (=rectangular) distribution. All values in between these bounds have the same likelihood.
3. Normal ("N")
The Low is interpreted to be the P90 value of this distribution. The Middle value is the mean and the high value is the P10 percentile. The range between High and Low is equal to 2.564 standard deviations.
4. Lognormal ("L")
The Low is interpreted to be the P90 value of this distribution. The Middle value is the (linear) mean and the high value is the P10 percentile. The range between High and Low is equal to 2.564 standard deviations. Note that these estimates are not in log values. The input numbers are transformed into their logarithms. The normal distribution simulation is then used on these log values. The results are again the anti-log values and put into the vector.
5. Triangular ("T")
Here the Low, Mode and High values are the input. Note that the Mode should be the "most likely value". which may well be different from the mean of the median.

The letter indications may be also lower case. Always give three numbers as input. The meaning of the three numbers is dependent on the distribution type.

### Set path to input directory

The default path to the Volalc input is in the directory of the Volcalc program. If the user wishes to use another folder, he can use the Set Path option under "Options". This allows browsing for a directory/folder. His choice will be remembered after closing the Volcalc program in the "DefPath.txt" file in the VolcalcDefaults directory.

### Trap description

The trap description has the following options:

1. Simple trap models
1. Spherical segment
2. Cosine model
3. Cylinder model("Camembert")
4. Monocline
5. Paraboloid
2. Contoured traps
1. Anticline
2. Strattrap
3. External Gross Reservoir Volume (GRV)
used if the volume has been calculated by some other programme. The above figure shows the trap input input grid when a contoured stratigraphic trap is described. For the culmination, the top of the reservoir at the highest point, the most likely depth from the main input sheet must be chosen. The areas of the top reservoir are always greater than, or equal to those for the base at the same depth row. If OFU units are used, the depth data are in feet, but the area units of square kilometers are for both metric and OFU. Saving your input will transform the depth in feet into meters. This results in a single geometrical reprersentation of the trap, quite contrary to the varying traps generated with the "simple trap models". However the Gross Reservoir Volume is varying because of variation in the Gross Reservoir Thickness. The variation in depth is used by the program in estimation of various PVT variables. Schematically, the contoured trap models are shown below:

Anticlinal structure Stratigraphic trap  Note that for the stratigraphic trap, the areas for the top reservoir are taken from a vertical plane (vertical line in the figure) through the culmination. These are areas that include the yellow and white zone in the figure. The areas for the base reservoir are taken from the same vertical plane, but include only the white area. Top reservoir areas can only be equal, or greater than the base reservoir areas.

#### Dip on the flank

As a check on reality, both the dip on the flank at spillpoint and the maximum dip observed between culmination and spillpoint of a trap is calculated. For this purpose a width of the trap is estimated from the area at a given depth. As for all trap models, the trap is subdivided into 1000 "slices" between culmination and spillpoint, the difference between successive half "widths" and the thickness of the slice gives a tangens of the dip. The area is in this case is approximated to be a circle.

### Appraisal options

The three appraisal models are:

1. Hydrocarbon Column
For this option input in both the HC column and the Gascap% rows is required. This option fills the trap down to the length of the HC column. Then uses the gas column % to get the length of the gas column and from that the volume of the gascap. The oil ring volume is found by substraction of the gascap volume from the total HC volume. These calculations are, of course, done with the Gross Reservoir Volume (GRV).
2. Hydrocarbon Contact
This option uses the position in depth of the contacts to estimate the gross reservoir volumes with gas and oil. The required inputs are the depth of the Oil/Water contact OWC (which mabe the GWC if there is only gas) and the Gas/Oil Contact (GOC). This information is equivalent to the lengths of the HC columns, and hence leads to the volumes in the same way as in the Column Option.
3. Trapcapacity for Oil
This option calculates the Gross Reservpoir Volume GRV and fills it to spillpoint with Oil. The result is a listing of oil in place, recoverable oil. It is a pure trap capacity exercise for oil. hence the only POS figures are the POSv, because no subjective POS input is relevant in this case.
This is similar to the trap capacity for Oil above.

### World-wide Default Priors

World-wide priors are available for:

• Oil density, API gravity
• Condensate richness (Condensate ratio)
• Recovery efficiency Oil
• Recovery efficiency Gas
• Recovery efficiency Condensate.

The oil density regression has been based on a world-wide sampling from some 80 sedimentary basins. The result is a simple regression of API gravity on depth in meters and a fairly large standard error of estimate.

The condensate ratio is based on some 73 examples of condensate reservoirs, where temperature and pressure were available. The regression of the ratio on T and P, although expected to be helpful, is not significantly better than a regression on only P. This is because of the strong correlation between P and T, both largely determined by depth. The Pressure (P) explains some 45% of the variance. The standard error of estimate is as high as 69.5 b/MMcf. The problem with the data is that samples are only available for cases with condensate. Under the same conditions of P and T it is very well possible to have no condensate at all, depending on the petroleum system elements, such as maturity, origin of the gas (bacterial gas will be very dry), etc. Therefore this default estimate is only meaningful under the conditional probability of having condensate, given free gas. That estimation of the conditional P[Condensate|Free Gas] must be based on analogons and geological insight.
The regression in terms of OFU units is:

CGR = -67.78 + 0.0244*P +/- 69.5

The recovery priors are simply histograms on a world-wide basis, so having a mean and a standard deviation.

### Monte Carlo procedure

The Monte Carlo procedure uses 10,000 cycles as a maximum. In the upper right of the input form is a box where a smaller number of cycles can be put, but this is normally not necessary; 10,000 is the default.
To see whether the accuracy of the various results is sufficient, or to take the inaccuracy into account when decision making, standard deviations are listed in the reults table. The uncertainty of the Mean values is dependent on the number of MC cycles. With the 10,000 cycles, the standard deviation of the mean of e.g. recoverable oil, is the standard deviation of the 10,000 simulated values, divided by 100 (100 is the square root of 10,000). For the Mean value after cutoff ("MSV, or Mean Success Volume) the standard deviation increases above that from the un-cut result by increasing cutoff. This is because less values are above cutoff and used to calculate the mean.

For the probabilities, (POSv) the situation is slightly more complicated, and, in this case only applies to the results after cutoff. Assume that the cutoff has left na values above cutoff. The (n - na) values are "failure" cases. Now the binomial distribution has a mean of na/n and a variance of [na(n - na)]/n. The exact confidence ranges of the POSc are difficult to calculate. However, a normal approximation of the binomial distribution can be used to estimate the accuracy within certain bounds. If na is small in comparison with n, the accuracy can suffer considerably. The standard deviation of the POSv as listed can be used as a guide to accuracy. The uncertainty of the POSv is modeled as a normal distribution, because of the large number of Monte Carlo cycles used. This distribution has the following parameters, where p = POSv: ### Output The output is given as four tables, with in the upper part the usual statistics of interest, such as the P90, P50, P10 values and the Mean ("unrisked Expectation").

The Metric and OFU list of recoverable hydrocarbons

1. Parameter
2. Recoverable Oil
3. Recoverable Free gas
4. Recoverable Condensate
5. Recoverable Oil after oil cutoff
6. Recoverable Free Gas after gas cutoff
7. Recoverable Condensate after gas cutoff
8. Oil equivalent (Sum of Oil, Condensate and all combustible gas in terms of energy equivalent).

The Metric and OFU list of In Place Hydrocarbons

1. Parameter
2. BRV (or GRV) the gross reservoir volume
3. STOIIP, the Oil in place
4. SGIIP, the Solution gas in place (as a product of GOR and STOIIP)
5. FGIIP, the free gas in place
6. TGIIP, the total gas in place

In the lower part of the tables a summary list at 5% intervals of the expectation curve is given. With this data an expectation curve can be viewed by clicking on the heading of a table column. The first three rows give the percentiles of the unrisked expectation curve: P90, P50 and P10. For some programs any addition of prospect reserve estimates are based on these numbers. The the green highlighted row gives the Mean values ("unrisked means"). The next three rows give the minimum, mode and maximum, which can be interpreted as the parameters of a triangular distribution. The follows a row with the standard deviation and the standard deviation of the Mean. The latter is derived from the standard deviation, divided by the square root of the number of Monte Carlo cycles.
The pink highlighted row gives the POSv, the probability of success of the volume itself. If there are no zeros generated, this POSv is 1.000, but occasionally, a distribution model creates impossible negative values. The program sets such values to zero. The POSv is then less than one.
The POSv becomes more important in the last three columns, because there the results are affected by their respective cutoffs. The standard deviation of this POSv is also calculated and displayed in the next row. This value is only relevant for the POSv, because for the POSg we have a single subjective estimate, the uncertainty of which is difficult to know, or, in any case the user is not asked for such information (to keep things simple).

The last two rows are:

• The POSg, basically the subjective POS input of the user and the product of the primary chance factors. However, for the BRV we only use the product of the Probability of a trap and of a reservoir. For the POSg of Free Gas the conditional P[Free Gas | HCcharge] is multiplied with the overall POSg. The POSv for Condensate is the product of the POSg with the conditional P[Condensate | Free Gas].
• The POSc, which is the product of the POSv and POSg. Without a cutoff, the POSc is often equal to the POSg, but in the last three columns the values are usually different, the POSc being lower than POSg.

The lower part of the results table contains a 21-point representation of the expectation curve for each of the categories (Columns). This summary of the total distribution of values is used for estimating the mode and to produce the "unrisked" expectation curve graph (by double clicking on the column header). Both a Metric and an OFU table of results is provided.

### Saving Input and Output

The input file consists of a title to identify the run, the filename and a list of all the cells of the input grid, with coordinates and cell content, in a textfile. There is no facility to file the output. Saving in and output can also be done by clicking the "Clipboard" button. Then the datagrids can be pasted into a worksheet for further refinement, display or printing.

### Printing In- and Output

The most convenient way to print input and results is to copy the table and paste it in Excel. Use the "Clipboard" button to copy. Then the column width may have to adjusted, but all the advantages of the Excel mechanisms for selecting and printing are available. So you have to use the mouse to select the cells of the datagrid and then copy it to the clipboard by [Ctrl] and "C".

The more direct way to print results is to use the menu Print item which allows the printing of:

1. Input - in portrait mode on one page. >/li>
2. Recoverable hydrocarbons - Metric units, in landscape mode, one page
3. Recoverable hydrocarbons - Oil Field Units, in landscape mode, one page
4. In Place hydrocarbons - Metric units, in portrait mode, on page.
5. In Place hydrocarbons - Oil Field Units, in portrait mode, on page.
6. Unrisked Expectation Curve - Select by clicking on the column header in a result table.

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Date 22-02-2015.