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Predicting performance of in-situ combustion

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Predicting the production response to in-situ combustion (ISC) has been the topic of various studies. Complete numerical simulation of in-situ combustion is difficult because of the complex reactions and the thin burning front that requires small gridblocks for representation.

Prediction methods

Simulators range from tank models to complex 3D simulators. In addition to simulation, the following have been developed:

  • Empirical models
  • Hybrid models
  • Correlation methods

The easiest method is essentially a tank balance,[1] adapted by Prats.[2] The oil and water produced are given by





  • Soi = initial oil saturation, fraction
  • Sf = oil saturation burned, fraction
  • Vb = volume burned, m3
  • Np = oil produced, m3
  • Wp = water produced, m3
  • Ф = porosity, fraction
  • Vp = volume of the pattern, m3
  • Swf = water saturation resulting from the combustion process, fraction

If the volumes are in acre-ft and the production terms are in bbl, a multiplication factor of 7,758 must be used. The estimate of 40% of the oil produced coming from outside the burned volume is an empirical value based on experience. This is the 0.4 term in Eq. 1.

Fig. 1, presented by Gates and Ramey,[3] combines laboratory results and field observations from the Belridge in-situ combustion projects. It shows the effect of initial gas saturation on the oil recovery history. Oil production rates and instantaneous air/oil ratios can be estimated from the slopes of the curves. At late times, the above two techniques give similar results.

Satman and Brigham[4] used data from dry combustion field tests to obtain two empirical correlations. Those are presented in Figs. 2 and 3. The terms in the ordinates are cumulative incremental oil produced (CIOP), original oil in place (OOIP), fuel burned (FB), and oil in place (OIP) at the start of the project.

In addition to original oil saturation So, thickness h, oil viscosity μo, and porosity Ф, the abscissa includes cumulative air injected (CAI), and OIP at the start of the project, and fraction oxygen use. The second correlation, Fig. 3, is the most accurate except for oils with less than 10 cp original viscosity, where the first correlation must be used. These correlations were generated from pilot floods; thus, they would not be expected to be accurate for pattern flooding. However, pattern flooding is generally not the best way to operate an in-situ combustion project, and these correlations are expected to be reasonably accurate for line-drive projects.


Np = oil produced, m3
Sf = oil saturation burned, fraction
So = oil saturation, fraction
Soi = initial oil saturation, fraction
Swf = water saturation resulting from the combustion process, fraction
Vb = volume burned, m3
Vp = volume of the pattern, m3
Wp = water produced, m3
Ф = porosity, fraction


  1. Nelson, T.W. and Mc Neil, J.S. 1961. How to engineer an in-situ combustion project. Producer Monthly (May; Oil & Gas J. (5 June).
  2. Prats, M. 1982. Thermal Recovery, Vol. 7. Richardson, Texas: Monograph Series, SPE.
  3. 3.0 3.1 Gates, C.F. and Ramey Jr., H.J. 1980. A Method for Engineering In-Situ Combustion Oil Recovery Projects. J Pet Technol 32 (2): 285-294. SPE-7149-PA.
  4. 4.0 4.1 4.2 Brigham, W.E., Satman, A., and Soliman, M.Y. 1980. Recovery Correlations for In-Situ Combustion Field Projects and Application to Combustion Pilots. J Pet Technol 32 (12): 2132-2138. SPE-7130-PA.

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See also

Operating practices for in-situ combustion

Laboratory studies of in-situ combustion

Predicting behavior of in-situ combustion

In-situ combustion