APPLICATION OF PVT CORRELATIONS TO MATERIAL BALANCE

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PVT properties are always determined experimentally based on actual samples collected from either well bore or at the surface. Such samples may be very expensive to obtain. Hence, in case of the absence of the experimental measurements of PVT properties, it is necessary to use the empirically derived correlation to predict the PVT data (T. Ahmed, 2001). Common practice in a lack of PVT measurements for the entire range of pressure and temperature has been the use of PVT correlations. Correlations provide qualitatively correct description of the basic properties of oil but require adjustments to specific fields (Khabibulin & Khasanov, SPE 2014).

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APPLICATION OF PVT CORRELATIONS TO MATERIAL BALANCE PREDICTIONS:

APPLICATION OF PVT CORRELATIONS TO MATERIAL BALANCE PREDICTIONS 1 ESSIEN M. ANIEKAN BY ENG1105540 SUPERVISED BY: ENGR ADEWALE A. ADENIJI

OUTLINE OF PRESENTATION:

OUTLINE OF PRESENTATION INTRODUCTION AIMS & OBJECTIVES OF STUDY SCOPE OF STUDY LIMITATION OF STUDY PROBLEM STATEMENT METHODOLOGY OF STUDY RESULTS DISCUSSION & CONCLUSIONS RECOMMENDATIONS 2

INTRODUCTION:

INTRODUCTION PVT properties are always determined experimentally based on actual samples collected from either well bore or at the surface. Such samples may be very expensive to obtain. Hence, in case of the absence of the experimental measurements of PVT properties, it is necessary to use the empirically derived correlation to predict the PVT data (T. Ahmed, 2001). Common practice in a lack of PVT measurements for the entire range of pressure and temperature has been the use of PVT correlations. Correlations provide qualitatively correct description of the basic properties of oil but require adjustments to specific fields (Khabibulin & Khasanov, SPE 2014). 3

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According to (Sunday , Madu & Lanre SPE, 2006 ), one can resort to empirical PVT correlations to examine the reservoir fluid in the following cases: Inability to obtain a representative sample Sample volume is insufficient to obtain a complete analysis Quality check laboratory analysis Laboratory analysis are in error Estimating the potential reserves to be found in an exploration projects Evaluating the original oil in place and reserves for a newly discovered area before obtaining the laboratory analyses to justify a primary development plan.   To perform material balance calculations, production data, pressure data, PVT data, and any remaining reservoir characteristics are required. If any one of these data sets contain errors or inaccuracies, it will have an effect on the outcome of the material balance equation i.e ± OOIP = f (drive mechanism, Δ P , Pressure errors, PVT errors , Production data errors) (CIPC , 2003).   4

AIMS & OBJECTIVES OF STUDY:

AIMS & OBJECTIVES OF STUDY The main aim is to apply PVT correlations to Material Balance Predictions . Others are: Prediction of PVT data using Black oil PVT Correlations PVT error estimations Integration of Quantitative (statistical error) and Qualitative (Performance plots) to perform PVT matching. Investigation of the effect of PVT errors on OOIP 5

SCOPE OF STUDY:

SCOPE OF STUDY This research covers PVT matching using correlations and Cross plots. Also , the work focuses on application of the PVT data (correlations) to material predictions and comparison between the OOIP from the Predicted and Measured PVT data . 6

LIMITATIONS OF STUDY :

LIMITATIONS OF STUDY There was time and cost constraint . The availability of high data processing computer to run large number of calculations was a limiting factor . There were restrictions on data of such valuable operations outside the industry . The complexity of parameters in the PVT correlations presented challenges which led to personal and computational errors. 7

PROBLEM DESCRIPTION:

PROBLEM DESCRIPTION Errors are incurred in using PVT correlations for material balance prediction. Therefore, such errors must be quantified using statistical estimations and cross plots in order to investigate the deviation from the actual PVT data. Also , selection of appropriate PVT correlations to best predict the PVT data via PVT matching in order to reduce errors incurred in OOIP. 8

METHODOLOGY OF STUDY:

METHODOLOGY OF STUDY SOURCES OF DATA The data used in this research work were collected and collated from secondary sources for analysis and interpretation. They were sourced from textbooks, internet and Research papers. Specifically, the field data such as Reservoir Performance data, Water Influx History and PVT data were modified from Petro-wiki for West Texas oil field. TYPES OF PROCEDURE/APPROACH In this work, the descriptive and analytical approaches were used to determine the objectives. The descriptive approach involved the explanation of certain concepts like application of PVT correlations and OOIP predictions, etc. With the analytical approach, mathematical formulae, tables, pictures and plots were used for data presentation, analysis and interpretation. 9

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METHOD OF DATA ANALYSIS This involved the use of mathematical formulae, material balance equations, various PVT correlations and statistical techniques to analyse the data. PROCEDURE OF CALCULATIONS The formula used to solve the problem was executed using Microsoft Excel Spreadsheet MBE 10

RESULTS:

RESULTS GLASO STANDING VAZQUEZ-BEGGS AL-MARHOUN PETROSKY-FARSHAD 49.6% 39.9% 46.9% 50.5% 41.1% 11 TABULAR PRESENTATION OF RESULTS SOLUTION GOR OIL FVF GLASO STANDING VAZQUEZ-BEGGS AL-MARHOUN PETROSKY-FARSHAD 2.9% 1.8% 2.3% 2.7% 1.9% GLASO STANDING VAZQUEZ-BEGGS AL-MARHOUN PETROSKY-FARSHAD 89.3% 55% 71.98% 68.0% 54.1% BUBBLE POINT PRESSURE

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12 OOIP GLASO S STANDING VAZQUEZ-BEGGS AL-MARHOUN PETROSKY-FARSHAD 86.9% 18.7% 31.6% 12.4% 85.6% GRAPHICAL PRESENTATION AND INTERPRETATION OF RESULTS PVT MATCHING Solution GOR, Rs

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OIL FVF 13

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OOIP 14 Combining the plot above with the Average Absolute Relative Error for OOIP, it was observed that AL-MARHOUN correlation gave the best match with an AARE of 12.4% followed by STANDING correlation with an AARE of 18.7 % .

DISCUSSIONS & CONCLUSIONS:

DISCUSSIONS & CONCLUSIONS SOLUTION GOR Between 1640psia and 800psia, STANDING produced the overall best match followed by PETROSKY-FARSHAD with an AARE of 39.9% and 41.14% respectively. OIL FVF Between 1640psia and 800psia, STANDING produced the overall best match followed by PETROSKY-FARSHAD with an AARE of 1.8% and 1.9% respectively BUBBLE POINT PRESSURE Between 1640psia and 800psia, STANDING produced the overall best match followed by PETROSKY-FARSHAD with an AARE of 53.0% and 54.1% respectively. 15

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OOIP Between 1640psia and 800psia, AL-MARHOUN produced the overall best match followed by STANDING with an AARE of 12.4% and 18.7% respectively. From the Overall match it could be concluded that AL-MARHOUN produced the best match for OOIP followed by STANDING correlation. However , STANDING correlation proved to be the best at matching GOR and Oil FVF but did not produce the best match for OOIP. Therefore, there is a need to apply the PVT correlations and make selections prior to the application rather than simply inferring directly from the PVT matching in order to reduce errors incurred in its application . However , for the purpose of limited time and resources, the STANDING correlation could be used directly from PVT matching since it also gives a minimum error in OOIP. 16

RECOMMENDATIONS:

RECOMMENDATIONS Data can be obtained from more wells for a more comprehensive analysis. It is important for the engineer to have basic curve fitting procedures for laboratory data analysis. More Investigations need to be carried out on the influence of viscosity on recovery efficiency. More statistical tools and techniques can be used to supplement the techniques applied in this research work . 17

THANK YOU:

THANK YOU 18

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REFERENCES Ahmed T.: Reservoir Engineering Handbook , 2 nd Edition, Gulf Publishing Company, Texas, 2001. Al- Marhoun , M.A., “PVT Correlations for Middle East Crude Oils,” JPT, May 1988. Amaco Production Company “Fluid Sampling” Course Manuscript, Production Training Center , Tulsa, Oklahoma, Dec. 1982. Austin Ukwu , Kanu and Onyekonwu Mike obi “Advancement in Material Balance Analysis” Department of Pertroleum and Gas Engineering, University of Porthacourt , Nigeria, SPE-172415-MS, Presented at the SPE Nigeria Annual Technical Conference and Exhibition held in lagos , Nigeria, 05-07 August 2014. Bu, T. and Damsleth, E., “Errors and Uncertainties in Reservoir Performance Predictions,” SPE paper 30604 presented at the 1995 SPE Annual Technical Conference and Exhibition, Dallas, TX, October 22-25, 1995. Canada, June 10 – 12, 2003. Carlson, M.R., “Tips, Tricks and Traps of Material Balance Calculations,” JCPT , December 1997. Carlson, M.R.: “Tips, Tricks, and Traps for Oil Material Balance Calculations,” paper 95-07 presented at the 46 th Annual Technical Meeting of the Petroleum Society of CIM, Banff, Alberta, May 14-17, 1995. Cole, F.W.: Reservoir Engineering Manual , Gulf Publishing Co., p. 285 Houston (1969). Craft, B.C. and Hawkins, M.F., Applied Petroleum Reservoir Engineering , Second Edition revised by R.E. Terry, Prentice-Hall, Inc., Englewood Cliffs, NJ, 1991. Dake , L..P., The Practice of Reservoir Engineering , Elsevier Science B.V., 1994. Eissa m. el-m shokir , hussam m. goda , khaled a. fattah , and mohamed h. sayyouh “ Modeling Approach for Predicting PVT Data” Petroleum Engineering dept.,( king saud university, Curtin university of technology, Australia , Cairo University ) Journal of the University of Qatar, Vol. 17, 2004, pp.11-28. Glaso , O. “Generalized A Pressure-Volume-Temperature Correlations,” JPT May 1980. Havlena, D. and Odeh , A.S., “The Material Balance as an Equation of a Straight Line—Part II, Field Cases,” JPT , July 1964. 19

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J . L. Pletcher , Improvements to Reservoir Material Balance Methods SPE 62882, Marathon Oil Company (Retired), Presented at the 2000 SPE Annual Technical Conference and Exhibition held in Dallas, Texas, 1–4 October 2000. Petrosky , G.E and Farshad , F.: “Pressure-Volume-Temperature Conditions for Gulf of Mexico crude oils” SPE 51395, Presented at the SPE Annual Technical Conference and Exhibition, Houston, p.416-420, 3-6 october 1993. Pletcher , J.L., “Improvements to Reservoir Material Balance Methods,” SPE paper 62882 presented at the 2000 SPE Annual Technical Conference and Exhibition, Dallas, TX, October 1-4, 2000. R. Khabulin , M. Khasanov , A. Brusllovsky , A. odegor and D. Serebyakova “New Approach to PVT Correlation Selection” Gazpromneft NTC, V.krasnov , Rosneft , SPE- 171241-MS, Presented at the SPE Russian Oil and Gas Exploration and Production Technical Conference and Exhibition held in Moscow, Russia, 14-16 October 2014. R.O. Baker, C. Regier , R. Sinclair “ PVT Error Analysis for Material Balance Calculations” Epic Consulting Services Ltd presented at the Canadian International Petroleum Conference 2003, Calgary, Alberta, Standing, M.B. “A Pressure-Volume-Temperature Correlation for Mixtures of California Oils and Gases,” API, 1942. Sunday Sunday Ikiensikimama ; John Madu , SPE and Lanre Dipeolu , SPE; “Black oil Empirical PVT Correlations Screening for the Niger Delta Crude” SPDC Nigeria, SPE 105984, Presented at the 30 th Annual SPE Technical Conference and Exhibition held in Abuja, Nigeria, 31 July -02 August 2006. Vazquez , M.E. and Beggs , H.D. “Correlations for Fluid Physical Property Predictions,” JPT June 1980 20

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