Acoustic tomography for monitoring enhanced oil recovery

Justice, James H.; Vassiliou, Anthony; Singh, Satvinder; Logel, John D.; Hansen, Patricia; Hall, B. R.; Hutt, P; Solanki, Jaimin

doi:10.1190/1.1439605

Cited by 68 publications

(22 citation statements)

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“…Seimic tomography has been very succesful in monitoring EOR produced changes with respect to time. Excellent examples of the seismic mapping of steam injection and in-situ combustion processes can be found in Bregman, et al (1989), Justice, et al (1989 and Paulsson, et al (1992). Cross-well resistivity tomography has shown promise in monitoring both oil and environmental related steam injections (Beasley and Tripp, 199 1, Shima and Imamura, 199 1, Ramirez, et al, 1992) and Daily and Ramirez (1992) have found it useful for tracking the flow of ground water through the unsaturated zone.…”

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confidence: 99%

Iterative electromagnetic Born inversion applied to earth conductivity imaging

Alumbaugh¹

1993

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order Born approximation is applied to linearize the integral equations. From these simplified equations, sensitivity functions are derived which define the ability of the crosswell magnetic field measurements to detect small local changes in conductivity. Plots of the spatial variation in sensitivity indicate that vertical resolution is a function of the spatial sampling density in the vertical direction, while the horizontal resolution depends on the vertical separation between the source and receiver. Additional improvement in the horizontal resolution can be provided by making additional measurements with both the source and receiver in the same hole.Further sensitivity analysis is completed in terms of a dimensionless background induction number that is defined by oopl2 where o is the background conductivity and 1 is the source-receiver separation. Analysis of the crosswell sensitivity in terms of this parameter facilitates experimental system design for a given borehole separation and background conductivity, as well as the determination of the operating frequency which falls within an optimal range of oo@ 2.For oopl2 ~1 0 , the scattered fields are very small compared to the primary field, making measurements of the inhomogenous response very difficult in the presence of noise. In addition, a given source-receiver pair is sensitive to a large volume of strata outside of the interwell zone rather than just the region immediately between the probes. The latter property requires that a larger region be considered in the interpretation phase and that the proper 2-D or 3-D model geometry is employed. As the induction number is increased the nature of the sensitivity functions change. For oopl2 > 50 a given source-receiver pair is sensitive only to a "ray-path" shaped zone immediately between the two probes and the scattered fields are on the same order of magnitude as the primary fields. Unfortunately the attenuation at these large induction numbers prevents accurate measurement of the fields for large vertical probe separation due to the dynamic range limitations of the measurement system.The validity of using a 2-D cylindrical model to simulate a generally inhomogenous earth is investigated by comparing the 2-D Born series solution to other 1-D, 2-D and 3-D modeling algorithms. For ooyl2 < 50 the size of the region outside of the wells that is included in the model has a significant effect on the properties of the calculated EM fields with the different model geometries producing significantly different results. At larger induction numbers (owpl2 >50) a given source-receiver pair senses only the medium directly between the probes and the resulting fields are fairly independent of whether a 1-D, 2-D or 3-D model is employed. Unfortunately at these large induction numbers the Born series does not readily converge.To image the subsurface conductivity smcture between two wells, the 2-D cylindrical Born series approximation is incorporated into an iterative Born inversion scheme. The inversion problem is stabiliz...

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confidence: 99%

Iterative electromagnetic Born inversion applied to earth conductivity imaging

Alumbaugh¹

1993

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“…Porosity and permeability mapping Barclay et al (2008) Anomalous pore pressure detection Landrø and Kvam (2002) Fracture detection Blackburn et al (2007) Tracking thermal fronts Zadeh, Srivastava, Vedanti, and Landrø (2010) Gap cap movement Albright et al (1994), Barkved (2004) Water flooding Leggett et al (1993) Steam reservoir boundaries Justice et al (1989), Albright et al (1994), Brzostowski and McMechan (1995) Distribution of permafrost Acknowledgements I would like express my gratitude to Schlumberger for permission to publish this book chapter, and to several Schlumberger clients for permission to reuse some figures containing their data. Thanks to Lisa Stewart, executive editor of Schlumberger Oilfield Review, for her help in the preparation of this chapter.…”

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Applications of tomography in oil-gas industry – Part 1

Xie¹

2015

Industrial Tomography

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“…One of the major difficulties for reconstruction algorithm design is that the sensor locations are spatially sparse, i.e., limited to the locations of injectors/producers, while the flow velocity contrast between the layers is very high. If we use a cell based inversion (Justice et al 1989) method, which divided the volume into small cells, the result will be a very blurred image, where it will be hard to identify the shale discontinuities.…”

Section: Reconstruction Algorithmmentioning

confidence: 99%

Detecting Shale Discontinuity between Different Layers Using Waterflood Tomography

et al. 2012

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This paper presents a novel signal processing method to detect the existence and location of shale discontinuities between layers with distinct permeabilities by using only waterflood injection and production data. Continuing the work by Y. Lin, et. al (SPE-132699-PP), we use a new waterflood tomography concept to analyze cross-flow behavior among different layers and estimate the hydraulic transmissivity via tomography mapping. With designed injection rates, we estimate the response times at the producers by monitoring production rates. The response time represents the `cost' for the fluid to travel between well-pairs and we can use it to model the virtual path through different layers. We consider the case of waterflooding in the presence of permeability contrast in different layers. The fluid in the low permeability layer tends to flow through the shale discontinuity to the higher permeability layer thus forming vertical `high permeability cross-flow channels between the wells. With the response time, we are able to identify these 3D high perm channels to estimate the location of shale discontinuities causing the cross-flow. To the best of our knowledge, we are the first to propose this waterflood tomography method. Without significantly affecting daily operation and without the cost associated with tracer testing and seismic tomography, our technique only involves applying scheduled changes to the injection rates and analyzing the relationship between these changes and those in production rates.To demonstrate the application, using a commercial simulator, we build a double layer reservoir model with different permeabilities. We test a line drive case with injectors and producers having perforations in both lower and upper layers. By applying our designed injection and shut-in schedule, we show our method can provide a very accurate estimate of shale discontinuity location by recording accurate response times between well-pairs.

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Acoustic tomography for monitoring enhanced oil recovery

Cited by 68 publications

References 0 publications

Iterative electromagnetic Born inversion applied to earth conductivity imaging

Iterative electromagnetic Born inversion applied to earth conductivity imaging

Applications of tomography in oil-gas industry – Part 1

Detecting Shale Discontinuity between Different Layers Using Waterflood Tomography

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