# Reservoir simulation assignment

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Engineering

Published on November 11, 2014

Author: ParvezNophel

Source: slideshare.net

## Description

A small presentation of History matching and a case study on it. Also on Gas material balance equation

1. RESERVOIR SIMULATION Assignment on 1. History matching and prediction 2. MBE with emphasis on Gas reservoir BY PARVEZ NOPHEL B.TECH APE UP (2011 - 15) R870211019 500017479 1

2. CONTENTS  WHAT IS RESERVOIR SIMULATION?  SIMULATOR AND ITS TYPES  HISTORY MATCHING AND PREDICTION  CASE STUDY  MBE  MBE FOR GAS RESERVOIR  EXAMPLE NUMERICAL ON GAS MBE 2

3. WHAT IS RESERVIR SIMULATION:  A digital description of reservoir together combined with physical and mathematical equations along with good reservoir engineering which is used to predict the future performance of the reservoir and hence managing the asset is called reservoir simulation  Reservoir simulation deals with solving set of equations, a representative of reservoir, using computer programming called simulator. 3

4. SIMULATOR AND ITS TYPES Simulator is nothing but mathematical equations solving by the execution of set of computer programs.  Black-oil model (IMEX)  Compositional model (GEM)  Thermal model (STARS)  Chemical  Miscible  Dual Porosity  Dual permeability 4

5. HISTORY MATCHING AND PREDICTION  History matching is the process of building one or more sets of numerical models (representing a reservoir) which account for observed, measured data.  It is a part of Uncertainty quantification.  It matches the developed model with geospatial, geological and production data to create a perfect reservoir model.  The matched model is used for future performance of the reservoir. 5

6. Figure 1. 6

7. CASE STUDY Organization: TNO - 1996  As the History matching is a process of selection of appropriate model for the future prediction, it should be more accurate.  Proper parameterization of the stochastic process involved.  The model parameter is assigned as show in the figure 1 which is an iterative process.  The data consistent with many models.  Subjective decision was made by the reservoir engineer. 7

8.  The uncertainty in any prediction cannot be assessed from just one model.  One point selection / base case.  The study demonstrates how limited and biased that practice is. Yet, most long-term forecasts are still based on a single history-matched.  Sometimes the best matched results may be improper due to the reason that the statistical nature of history matching and the inherent bias in the history-matching workflow are ignored. 8

9. TNO’S NEW METHOD: AN AUTOMATIC PROBABILISTIC HISTORY-MATCH PROCEDURE:  An automatic probabilistic history-match and prediction procedure has been implemented by TNO.  This procedure automatically generates many realisations of the reservoir reproducing the history data with satisfactory accuracy.  Using these realisations, predictions are derived and processed into an expectation curve.  Most of the theory behind this methodology has been developed and demonstrated on synthetic cases within the Production forecasting with Uncertainty Quantification project (PUNQ) 9

10. 10

11. Traditional history matching, keeps geological model along with the geological data out of the loop. Modern history matching, keeps geological model along with the geological data in the loop. 11

12. RESULTS OF TNO’S WORKS:  The geo- spatial data is correlated with the fluid flow model with least uncertainty by using PUNQ.  25 values are optimized by using PUNQ for just one parameter – Water production.  This produces accurate model for the future prediction of the reservoir.  Thus a successful history matching is achieved. 12

13. MBE: o Law of conservation of mass forms the basis for the MBE calculations for a reservoir estimation. o Predict future reservoir performance under various drive mechanism. ADVANTAGES OF MBE: The material balance equation and its many different forms have many uses including:  Confirming the producing mechanism  Estimating the OOIP and OGIP  Estimating gas cap sizes  Estimating water influx volumes  Identifying water influx model parameters  Estimating producing indices. 13

14. MBE FOR GAS RESERVOIR ([Solution gas present in the reservoir initially(st. vol.) ] + [Free gas present in the reservoir initially (st. vol.)] - [Gas produced (st. vol.) ] + [Gas injected (st. vol.)] ) ([Solution gas present in the reservoir finally (st. vol.)] + [Free gas present in the reservoir finally (st. vol.)] ) = 14

15. CONCEPT  COMPRESSIBILITY OF GAS IS VERY SIGNIFICANT DRIVE MECHNISM IN GAS RESERVOIRS AS COMAPRED TO RESERVOIR PORE VOLUME.  IF THERE IS NO WATER DRIVE IN THE RESVOIR, THE CHANGE IN PORE VOLUME WITH PRESSURE IS NEGLIGIBLE  EQUATION FOR THE VOLUME OF THE GAS IN RESERVOIR IS A FUNCTION OF PRTESSURE. 15

16. EQUATION FOR GAS MBE In gas reservoir oil volume is zero, thus the following is derived from Generalized MBE : Water and Formation compressibility is negligible when compared to gas compressibility For volumetric reservoir, We and Wp will become zero. 16

17. REFERENCES:  “Principles of Applied Reservoir Simulation”, Second edition; Fanchi, R. John; Gulf Professional publishing, Elsevier, USA; 2001.  http://www.streamsim.com/technlogy/history-matching/  http://www.streamsim.com/technology/sentivity-analysis- and-screening/  “Production forecasting with uncertainty quantification” – TNO. – http://www.tno.nl/downloads%5C309beno.pdf 17

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