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# FYP Final Presentation

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#### Transcript of FYP Final Presentation

Final Year Project
Final Presentation

Supervisor: Dr.Mohammed Abdallah Ayoub
External Examiner: Mr. Chander Shekhar Singh
Internal Examiner: Dr. Saleem Qadir Tunio

Introduction
The Scope of the study, Relevancy and Feasibility of The Project
LITERATURE REVIEW

Discussion Sections
- Introduction & Background.

- Problem Statement & Objectives

- Literature Review

- Methodolgy

- Results and Discussion

Conclusion & Recommendations

- Q&A
Introduction & Background
Numerous production engineering and reservoir analysis problems have been solved by estimating formation volume factor for oil-gas mixture. It is one of most important factors of physical properties of hydrocarbon.

Problem Statement
Integrated Report (Preview)
The END
Q & A
A new correlation for formation volume factors of oil and gas mixtures using GMDH
An empirical approach

Formation Volume Factor (FVF) can be defined as the ratio of the volume of oil plus the gas in solution at the prevailing reservoir temperature and pressure to the oil at standard condition. (Ahmad, 2000).

Many methods have been proposed to estimate the formation volume factor for oil-gas mixtures in the last decades(but they still can’t be risen to a level of the most accurate correlation).
Measuring the formation volume factor experimentally is not an optimal option.
The empirical approach is the most widely used nowadays to develop a new correlation for such parameters.
Objectives
Revising the best available correlation and defining the correlation parameters.

Understating the parameters influencing formation volume factor for oil and gas mixture.

To develop new correlation for Bo through GMDH method using minimum parameters as possible .

Evaluate the model performance by comparing the obtained results with the measured ones
The Relevancy of the Project
The new model will be helpful for solving production engineering and reservoir analysis problems.

Feasibility of the Project
The scope of this study is to develop new correlation for oil FVF of oil and gas mixture with more accurate results using minimum parameters as possible

Scope of the Study
This project requires a modelling software in order to conduct a successful study. By using MATLAB Software -which is available in UTP.

The project is clearly feasible to be implemented and results have been
obtained within the proposed time frame.

Standing 1947
Parameters: Rs, T,
Data: By using nonlinear multiple regression analysis for more than 160 experimental data.
Al-Marhoun 1988
Who am I ?
Matrik no: 15790
Course:Petroleum Engineering
Major: Drilling and Production Engineering
developed by Prof Alexey G. Ivakhnenko (1968) in the Institute of Cybernetics in Kiev (Ukraine).
Parameters: GOR, , and T.
Data: California oil field, 105 experimental data point, 1.2% average error.

LITERATURE REVIEW conclusion

Alshammasi 1999
ALshammasi oil FVF with 4 Parameters

Alshammasi oil FVF with 3 parameers

Why Important?

Show the ratio of volume of oil at reservoir to volume of oil at surface condition.
Relates directly to the calculation of oil initial in place under stock tank conditions (STOIIP)

Group Method of Data Handling (GMDH)
A computer-based method which a set of computer programs and algorithm were used to develop this approach with theoretical principles.
A GMDH; model with multiple inputs and one output
Mathematical approaches have been used in GMDH
The fluid properties for hydrocarbon fluids are obtained through laboratory analysis on a preserved or recombined sample of the reservoir fluid.
From literature review, this study learnt that the key parameters of input to predict Bo:
1. Reservoir Temperature
2. Gas solubility
3. Oil specific gravity
4. Gas specific gravity

Research Methodology & Activities
Key Milestone
Tools & Equipment
In this Project, MATLAB software (version R2013a) was utilized due to flexible programming and graphs visualization

Modelling Construction Process
Gantt chart
Project Methodology
The main activity of this project is to construct a model that can estimate the FVF for oil and gas mixture using GDMH approach.

Results & Discussion

Data Gathering

Model Development

Trend Analysis

Statistical Error Analysis

Scatter graphs
Schematic Diagram Of The Proposed GMDH Model Topology

Maximum absolute percent error (MaxAE).

Minimum absolute percentage error (MinAE).

Standard deviation of error (STD).

Conclusion
The GMDH model is successfully developed and the objectives of this study are successfully achieved.

The statistical & graphical error analysis have shown the GMDH model superiority over the other existing correlations and models.

The new developed GMDH model is very cost effective since the parameters need are reduced to two (2) only.

Recommendations
More improvements and developments in the GMDH code and process for predicting FVF will definitely lead to better and accurate prediction in the future. Hence, all focuses and researches is highly recommended to go through that direction.

The GMDH model is highly recommended to be incorporated in smart simulator.

GMDH model can be more accurate by collecting wide range of data from different fields.

Experimental work may be required to obtain data sets in order to predict the oil formation volume factor at below and above bubble point pressure.
REFERENCES
[1] Ahmed, T.,” Reservoir Engineering Handbook”; second Edition, Gulf publishing Company, Houston, Texas, 2000.
[2] Katz, D. L.: ’’Prediction of shrinkage of crude oils,’’ Dril. Prod. Prac. Am. Pet. Inst. Pp. 137-147 (1942).
[3] Standing, M.B., “A Pressure-Volume-Temperature Correlation for Mixtures of California Oils and Gases”; Drill and Prod., API, pp 275-286, 1947.
[4] Standing, M. B.: ‘’Oil-System Correlation.’’ Petroleum Production Handbook T. C. Frick (ed), SPE Richardson. TX (1962) 2. Chap. 19.
[5] Calhoun, J.C.,JR.,” Fundamentals of Reservoir Engineering”; University of Oklahoma Press, Norman, Oklahoma, 35, 1947.
[6] Vazquez, M.E., and Beggs, H.D., “Correlations for Fliud Physical Property Prediction”; JPT, pp. 986-970, June 1980.
[7] Glaso, O.,” Generalized Pressure-Volume-Temperature Correlations”, JPT, pp. 785-795, May 1980.
[8] Al-Marhoun, M. A.: ‘’PVT Correlations for Saudi Crude Oils,’’ SPE 13718, SPE Middle East Oil TECH CONF and EXHB (Manamah, Bahrain, 11-14 – March 1985)..
[9] Obomanu, D. A. and Okpobory, G. A.: ‘’Correlating the PVT Properties of Nigerian Crudes,” Tran ASME (1987) Vol. 109, pp 214-14.
[10] Al-Marhoun, M.A.,” PVT Correlatons for Middle East Crude Oils”, JPT, pp. 650-666, May 1988.
[11] Abdul-Majeed, G. H. A. and Salman, N. H.: ‘’An Empirical Correlation for FVF Prediction,” J Can. Pet. Tech., 27(6): 118-122 (1988).
[12] Al-Marhoun, M. A.,”New Coreelations Formation Volume Factors of Oils and Gas Mixtures”, JCPT, pp. 22-26, March 1992.
[13] Farshad, F. F, Leblane, J. L, Garber, J. D. and Osorio, J. G.:”Empirical Correlation for Colombian Crude Oils,” SPE 24538 (1992)
[14] Dokla, M. and Osman, M.: ‘’Authors’ Reply to Discussion of Correlation of PVT Properties for UAE crudes,” SPE Formation Evaluation (March 1993) pp 82; SPE paper 26316.
[15] Al-Fattah, Saud Mohammed and Al-Marhoun, M. A.: ‘’Evaluation of empirical correlation for bubble point oil formation volume factor,” Journal of Petroleum Science and Engineering. 11(1994) 341-350.
[16] 1A.A.Al-Shammasi, "Bubble point pressure and oil formation volume factor correlations," 1999.

[17] Ivakhnenko, A. G. (1966). Group Method of Data Handling a Rival of the Method of Stochastic Approximation. Soviet Automatic Control, 13, 43-71.
[18] Farlow, S. J. (1981). The GMDH algorith of ivkhnenko. The American Statistian, Vol.35, No.4, 210-215.
[19] Farlow, S. J. (1984). The GMDH algorithm,” in Self-Organizing Methods in Modeling: GMDH Type Algorithms. New York: Marcel-Dekker.
[20] "GMDH," [Online]. Available: http://www.gmdh.net/GMDH_his.htm. [Accessed 2013].
[21] "GMDH.net," [Online]. Available: http://www.gmdh.net/index.html. [Accessed 2013].

a0 = 1.03
a1= 0.000506
a2= 0.000356
a3= 5.75
a4= 3.9
a5= 4.04

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