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Cite this article: Philip IO, Christopher IA, Pius EA (2017) Simulation of Vital Petro-physical Parameters from SP LOGs Using Designed Computer Programme; None Conventional Approach. Chem Eng Process Tech 3(2): 1042.

*Corresponding author

Idibie O. Philip, School of Earth and Mineral sciences, Federal University of Technology, Nigeria, Email:

Submitted: 11 May 2017

Accepted: 28 August 2017

Published: 30 August 2017

ISSN: 2333-6633

Copyright© 2017 Philip et al.

OPEN ACCESS

Keywords•Water resistivity•Volume of shale•Hydrocarbon saturation•Visual basic language•Spontaneous potential

Review Article

Simulation of Vital Petro-physical Parameters from SP LOGs Using Designed Computer Programme; None Conventional ApproachIdibie O. Philip1*, Idibie A Christopher2 and Enikanselu A. Pius1

1School of Earth and Mineral sciences, Federal University of Technology, Nigeria2Department of Chemical Sciences, Edwin Clark University, Nigeria

Abstract

A computer programme (OMINISP) in Visual Basic (VB) language for computing formation water resistivity, Rw, volume of shale, Vsh, and hydrocarbon saturation, SH from Spontaneous Potential (SP) log has been designed, coded and tested. The aim was to develop a fast alternative approach of measuring Rw, Vsh, and SH devoid of the use of charts. The input data - bed thickness, mud resistivity, mud-filtrate resistivity, surface and formation temperatures, the static self potential (SSP), pseudo static self potential (PSP) and total depth (Td) of the well (WELL 4 AND WELL 5) in part of Niger Delta were derived from two digitized wire line logs. Data was also inputted from literature and the output was compared. The maximum percentage deviation was less than 4%. WELL 4, comprises four reservoirs and WELL 5, five reservoirs. In both wells, the values of Rw range from 0.010 to 0.241. In WELL 4, the values of Vsh range from 0.243 to 0.812. Reservoir A in WELL 4 has the highest cleanliness (less shale) while reservoir C is considered dirty (shaly). In WELL 5, the values of Vsh range from 0.152 to 0.752. Reservoir A in WELL 5 has the highest cleanliness (less shale) while reservoir E is considered dirty (shaly). The programme has therefore, provided a fast technique of estimating Rw, Vsh and SH and thus, reduces the subjectivity inherent in the use of chart for correcting formation thickness/cleanliness in petro-physical analysis.

ABBREVIATIONSSP: Spontaneous Potential

INTRODUCTIONComputer programme has become a widely tool utilized in

all facets of life, this is due to its importance in making life easier, faster, neat and stress free. The application of programme in geophysics is numerous as most of the methods use programme [1,2]. The calculation of formation water resistivity Rw, Volume of Shale Vsh and hydrocarbon saturation SH from Spontaneous Potential known as SP logs involves corrections that render the method stressful, cumbersome and time consuming because many charts are involved in the correction [3]. To say that the use of charts has been the general methods so far in this method of computation and has rendered the method stressful. The best method of overcoming these challenges is to utilize the modern technology by converting these corrections into simple mathematical equations, writing these equations into a programme code and finally design a friendly user-interface that can make it simple, easy and stress free to compute.

The interest of oil companies in reservoir evaluation is to calculate the volume of hydrocarbon in reservoirs and the calculation of hydrocarbon saturation in a reservoir depends on the value of water saturation, which requires formation

water resistivity for its computation. Due to this fact, formation water resistivity has been an important parameter in reservoir evaluation. The earliest electric log used in the petroleum industry was the spontaneous potential (SP) log, and has continued to play a significant role in well log interpretation [4,5]. By far, the largest number of wells today has this type of log included in their log suites. Primarily, the spontaneous potential log is used to identify impermeable zones such as shale and permeable zones such as sand. [4,5] However, SP logs have other applications; which include, determination of ‘formation water resistivity (Rw)’ and determination of ‘volume of shale (Vsh) in permeable beds’. An auxiliary use of the SP curve is in the’ detection of hydrocarbons by the suppression of the SP response’ [6].

According to Helander [7], formation water resistivity represents the resistivity value of the water (uncontaminated by drilling mud) that saturates the porous formation, and which is also referred to as connate water or interstitial water. It is known to generate the free water which supplies the energy for the water drive in reservoirs, and its resistivity is a variable depending on the salinity, temperature and whether or not, the formation contains hydrocarbons [8,9]. Generally formation water resistivity, (Rw) is one of the most vital parameters in open hole log analysis. It is required to calculate fluid or gas saturation in the pore spaces of reservoir rocks. Its value can range from 0.01 ohm-m to several ohm-meters at reservoir temperature [3].

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Visual basic (Visual Basic) offers integrated, interactive development environment (IDE) and it is very simple particularly as to executable codes, known to be easy to develop graphical user interfaces and also easy to connect them to handler functions provided by the application. There is an intuitively appealing view of the graphical user interface of the VB-IDE for the management of the program structure in the large and various types of entities (classes, modules, procedures, form). VB is a component integration language which is attuned to Microsoft’s Component Object Model (“COM”). The COM components can be incorporated or linked to your application’s user interface and also good for storing documents [10]. The work intends to use as input, parameters generated from SP logs from Niger Delta of Nigeria and particularly, to design a Visual Basic programme to calculate the value of Resistivity of formation water (Rw), Volume of shale (Vsh) and hydrocarbon Saturation (SH).

METHODOLOGY

Materials

The applications used for this project are Petrel 2009 and Visual basic.NET.

The materials used for this project are the SP logs and parameters gotten from log header such as BHT = bottom hole temperature, Rmfs = Resistivity of the mud filtrate at the surface, Tms = Mean surface temperature, Rms = Resistivity of mud at the surface, and Td = Total depth of the well. Log analysis calculations require values of resistivity, in particular mud filtrate resistivity (Rmf), drilling mud resistivity and formation water resistivity (Rw). Because temperature varies with depth and resistivity varies with temperature, this practice requires that resistivities be corrected for the appropriate temperatures at depth. Measured values of Rmf and Rm at the surface were corrected to various formation temperatures.

Presentation of SP curves

Four sand bodies were picked from well 4 while five sand bodies were also picked from well 5, respectively, as shown in Figure 1. Before picking the sand lithology, a baseline was established to see deflections of the SP curve to the right and left which was determined by the resistivity of the ‘mud filtrate Rmf’ and resistivity of the ‘formation water Rw’[11].

Designing the programme

The first step in the design of the programme was the design of the user interface. The programme consists of eight windows. Window 1 (design) to Window 4 (design) consist of the user - interface windows, while Windows 1.vb to Windows 4.vb consist of the code environment. The textboxes were used to input parameters and they were all named according to the parameters they receive. The written algorithms shown in Figure 2 were followed for conversion into visual basic. NET codes, and codes for series of operation were written in the code environment starting with declaration of variables on the public class.

Algorithm and structure of the programme

Step-to-step approaches in executing the programme were written in understandable language (English language). This was

used in drawing the structure of the program. The structure of the program was drawn using the appropriate figure for each execution. The algorithm and the structure are shown below.

Algorithm:

- Input parameters, BHT, Tms,TD, Rmf, Ri, h, SP ,PSP, Rm and D as presented in Table 1

- Step1: Determine formation temperature Tf of the formation, as Tf = Tms +gG(D/100)

- Step 2: Where gG (Geothermal gradient) = (BHT – Tms/TD) * 100

- Step3: Show the value of Tf

- Step4: Correct Rm and Rmf to formation temperature using the equation:

Rmm = Rm * (T1 +6.77/T2 +6.77) and

Rmff = Rmf * (T1 + 6.77/T2 +6.77)

- Step 5: Correct for thin bed-effect if Ri/Rmm> 5 and 3<h<50ft then

SPcor = 4(Ri/Rmm+ 2) 1/3.65 – 1.5/ h – (Ri/Rmm +11)/0.651/6.05 - 1.0 + 0.95

Multiply SP measured on log with SPcor , SSP = SP * SPcor

- Step 6: Calculate Rwe as Rwe = Rmff (10SSP/60 +0.133Tf)

- Step 7: Calculate Rw = Rwe + 0.131 * 10(1/log(Tf/19.9)-2/-0.5Rwe + 10(0.0426/log(Tf/50.8)

- Step 8: If the condition is not true then use SP measured on Log as SSP and go to step 5

- Step 9: Calculate volume of shale using Vsh = 1 – PSP/SSP

- Step 10: Calculate water saturation, SW = ( F * Rw)/Rt1/2

- Step 11: Calculate hydrocarbon saturation, SH = 1- SW

RESULTS AND DISCUSSION The results of this work are presented as codes and tables, and

they are discussed below. Two well logs (SP logs), labelled well 4 and well 5, were acquired from Omini oil field, Delta State, Niger

Well 4 Well 5

Figure 1 Well Logs Showing Marked Sand Bodies and Shale.

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Delta of Nigeria. The computer programme (OMINISP) was used in the computation of Tf, Rw, Vsh and SH. Four sand bodies were picked from well 4 and five from well 5. The input parameters were derived from two digitized wireline logs (WELL 4 AND WELL 5) in part of Niger Delta. Data was also inputted from a literature [4,5] and the output was compared. The maximum percentage deviation was less than 4%. Before picking the sand lithology, a baseline was established to see deflections of the SP curve to the right and left which was determined by the resistivity of the mud filtrate Rmf and resistivity of the formation water Rw. The SP curves acquired for the two wells are shown on Figure 1 and the values read from the curves are shown on Table 1.

Presentation of the computer programme

The programme consists of the user – interface and the code environment. At the user – interface environment, the user interacts with the programme and this environment consists of four windows. The codes of the programme were written in the code environment. In using the programme, the introduction page opens with four buttons, Exit, Rw, Vsh and Sw /SH buttons, respectively. The Exit button exits the programme when clicked and the other three buttons are clicked on to continue with the programme. The appendix section displays the programme code.

Computation of Vsh

The formula, Vsh = 1.0 - PSP/SSP in the algorithm was used in computing Vsh both in the charts method and the computer programme. Going by the results, in well 4, the values of Vsh range from 0.243 to 0.812. Reservoir A in well 4 has the highest cleanliness, presenting it to have less shale, which indicates high hydrocarbon potential [12]. While reservoir C is considered dirty, presenting it with high shale, which indicates less hydrocarbon

potential. In well 5, the values of Vsh range from 0.152 to 0.752 [12,13]. Reservoir A in well 5 has the highest cleanliness (has less shale) while reservoir E is considered dirty (shaly) [4,5].

Computation of SH

The Archie equation, SW = *[ ]F RwRt

1/2 was used in calculating water saturation, SW from which, hydrocarbon saturation, SH was calculated using the Archie equation, SH = 1- SW. From the results, the values of SH range from 0.234 to 0.852 in well 4, while in well 5, the values range from 0.235 to 0.912 as presented in Table 2, making well 5 to have higher hydrocarbon saturation and thus, good reserviours prospect [12,14,15].

Table 2 also shows that reservoirs C in well 4 and reservoir E in well 5 have the lowest hydrocarbon saturation, while reservoir A in well 4 and reservoir A in well 5 have the highest hydrocarbon saturation.

Generated results

The results generated by the programme are shown on Table 2. The programme has been successfully run and tested with input data from literature and nine reservoirs from two wells obtained from Omini oil field, Niger Delta of Nigeria. The computed results were compared with those earlier determined using the conventional charts method. It could be observed that the computed values of Tf, Rw, Vsh, and SH are reasonably in the range of values normally observed in the field with a percentage deviation of < 4%. This result is sufficiently reasonable and reliable for any scientific purpose. This lends credence to the suitability of the programme as a faster (few minutes), user friendly and highly viable option to the use of charts for determining formation water resistivity, volume of shale and hydrocarbon saturation from SP logs.

CONCLUSIONIn this work, a programme dubbed as OMINISP in visual

basic for computing formation temperature, formation water resistivity, volume of shale and hydrocarbon saturation from SP logs has been successfully developed and which is basically the idea behind this work. It can be run in both the Disk Operating System (DOS) or Windows environments. The input parameters are often read from log headers or measured from the SP log proper. It is capable of automatically correcting Rmf and Rm to formation temperature and correcting for bed thickness (where thickness is less than 3 meters) as well as converting spontaneous potential to static self-potential (for thin and dirty sands). Data from literature and two wells with nine sand bodies, from Omini Oil Field, Niger delta, have been employed in test-running the programme. The computed Tf, Rw, Vsh and SH values were compared with standard previously determined field and laboratory measurements. In all the wells, the maximum deviation between computed and other methods of measurement was less than 4%. This closeness suggests that the programme is workable, accurate, and sufficiently reliable and could serve as a quicker option to the method of determining Rw from SP logs using charts.

NO

YE

Start J

V

Read Input DataD, Td, BTH, h, Ri, Rm, Rmfs, Tms, Tf, and SP

SSP = SPRmff= Rmfs(

+6.77+6.77

)

Rwe = Rmff (10ssp/(60+0.133Tf)

iRi/Rm>5 and

3<h<50(hinft)

Rw= (+0.131 10[1/log ( /19 .9)]−2

−0.5 +10[0.0426 / ( /50 .8)] ).

PSP = SP

SPcor=[ 4 ( +2) ]1/3.65 − 1.5

ℎ−( +11) / 0.65 ]1/3.65 − 0.1+ 0.95

SSP = PSP X S

Vsh= 1.0 -

SW = [ ∗ ]1/2

SH= 1 – Sw

Stop

Figure 2 Flow Chart for Programme Execution.

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Table 1: Input Parameters for WELL 4 and WELL 5.

S/N Reservoir Depth(Td)(ft)

Bed thickness(ft)

SP(mv)

PSP(mv)

Ri(Ω-m)

Rt(Ω-m)

Well 4

1 A 6750 40.24 -40 -3.21 28.23 15.842 B 7000 45.12 -30 -7.81 33.00 20.633 C 7500 12.05 -48 8.51 15.61 30.424 D 8750 30.40 10 11.63 20.41 32.34

Well 5

1 A 6750 49.23 -70 -1.87 12.62 38.422 B 7000 14.00 -60 -21.60 45.65 40.113 C 7250 38.34 -40 30.27 23.16 42.344 D 7500 12.02 -20 15.11 11.67 50.475 E 8760 46.64 -40 28.11 19.67 60.67

For Well 4, BHT = 135o F, Rmfs = 0.51, Rms = 0.91, Tms = 60o F, Td = 9016ft For Well 5, BHT = 130o F, Rmfs = 0.61, Rms = 0.81, Tms = 60oF, Td = 9016ft PSP values were read from adjacent formations of the various reservoirs from SP log in Figure 1

Table 2: Computed Output of Tf, Rw, Vsh and SH.

S/N Reservoir Tf(oF) Rw Vsh SH

Well 4

1 A 122 0.21 0.243 0.8522 B 127 0.112 0.721 0.4123 C 130 0.045 0.812 0.2344 D 135 0.011 0.321 0.742

Well 5

1 A 138 0.241 0.152 0.9122 B 145 0.113 0.221 0.8113 C 150 0.024 0.341 0.6544 D 155 0.011 0.561 0.4525 E 160 0.010 0.752 0.235

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Philip IO, Christopher IA, Pius EA (2017) Simulation of Vital Petro-physical Parameters from SP LOGs Using Designed Computer Programme; None Conventional Approach. Chem Eng Process Tech 3(2): 1042.

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