2005_Y.pdf

SPWLA 46th Annual Logging Symposium, June 26-29, 2005

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IMPROVED LWD DENSITY IMAGES AND THEIR HANDLING FOR THIN BED DEFINITION AND FOR HOLE SHAPE VISUALIZATION

Nicolas Meyer, Steve Holehouse, Total, Andrew Kirkwood, Derick Zurcher, Roland Chemali, Jeremy (Jez) Lofts, Geoff Page, INTEQ

ABSTRACT The use of logging-while-drilling (LWD) imaging tools in both post drilling analysis and real-time decision making applications is becoming more commonplace. These applications provide benefits in a variety of disciplines ranging from drilling engineering to petrophysics. Since LWD images are acquired by rotating measurement sensors with the drill string, certain benefits over wireline pad tools, such as 360 degree borehole coverage and the ability to use multiple sensor types such as density, resistivity and gamma-ray, can be realized. However, these benefits are not without limitations. Artefacts and processing errors due to drilling parameters, borehole environment effects, image acquisition methods, and the inherent measurement physics can propagate errors into image interpretation. In particular standard density images tend to amplify artefacts from small borehole irregularities, and cause borehole shape and geological features to overwhelm each other.

This paper presents processing methods to turn these limitations to our advantage for two density image applications: wellbore shape characterization and thin bed analysis. The new processing achieves the following: a reduction in image artefacts using sensor depth and resolution matching techniques; an improved borehole shape computation that accounts for non-linear density measurement behaviour; and an image resolution enhancement predominantly based on use of gamma counts from short spaced detectors.

INTRODUCTION Density and gamma-ray LWD instruments, originally designed for measuring petrophysical parameters, have successfully evolved to provide high quality images. This evolution was accelerated in recent years by the increased use of rotary steerable systems for drilling high angle and horizontal wells. In such systems the LWD platform is rotated at high rate, thus facilitating the acquisition of images without interfering with the drilling process. In fact logging while drilling images have come to bring valuable information not only to the petrophysicist and to the geologist, but also to the drilling engineer in terms of well placement and wellbore stability.

The following key imaging applications have emerged that place different and sometimes contradictory requirements on the real time measurement and the post acquisition processing of data. This is particularly true for density imaging. Stratigraphical applications necessitate a high resolution image immune to artefacts from borehole shape and rugosity. By contrast, wellbore stability applications are based on characterizing hole shape irregularities with minimal contribution from the local formation density contrasts. Geologists are often satisfied with memory images downloaded after the run as long as they exhibit optimal spatial resolution, while geosteering engineers call for images in real time even if it entails some resolution degradation.

This paper focuses on two of the above cited requirements, namely: how to obtain a higher resolution image with minimal sensitivity to wellbore rugosity, and how to image wellbore breakout and shape irregularities. The first technique will be applied to thin bed analysis, and the second technique will be illustrated by 3-D views of borehole breakouts indicative of local stress.

PRINCIPLE OF DENSITY IMAGING

A density sensor optimized for operating on a rotating bottom hole assembly is shown in Figure 1. Gamma rays streaming from the source interact with the formation near the well bore. They undergo Compton scattering in direct relation to the density of the formation. Scattered gamma rays return to the near and far collimated detectors where they are counted and classified according to their individual energy level.

Figure 1: Rotational Compensated Density for LWD.

Far Detector

Near Detector

Gamma Source

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Each of the detectors provides an estimate of the formation density. The far detector measurement is less sensitive to the borehole fluid and closer to the actual formation density. The near detector measurement is more sensitive to borehole fluid and other borehole shape artefacts. The final tool reading known as Compensated Density is obtained by optimally combining the far detector and the near detector readings respectively to correct for mudcake, for mud filled annulus and for borehole rugosity.

The spatial response of the Near Detector is more finely resolved than that of the Far Detector.

Borehole imaging with LWD density takes advantage of the rotation of the bottom-hole assembly. The density sensor scans the near-wellbore formation along the azimuth and places the recorded data in individual sectors corresponding to predetermined angular positions (Minette, 1992).

Depending on the model of the tool, there are generally 8 or 16 consecutive sectors, covering the full circumference of the wellbore. In theory the image with the higher number of sectors will exhibit a finer resolution. In reality however, since a density log is a nuclear measurement, the individual sectors in a 16 sector configuration each receive fewer gamma rays, which sometimes leads to a less favourable signal to

noise ratio. Given the statistical nature of density measurement via gamma scattering, the number of sectors is not the only determinant factor of final image resolution. Actual sensor design and source strength play an equally important role. Ideally, the data are acquired for 16 sectors, and then the image is processed for optimal signal-to-noise ratio.

Figure 2 shows a density image displayed initially as a discretely segmented azimuthal density with only 8 sectors for clarity. In the raw unprocessed image the boxed colour coding varies from dark brown for low density, to bright yellow for high density. Interpolation between sectors converts the discrete blocks into a smooth realistic looking image in the second image track. The middle of the track corresponds to the low side of the hole as customary in high angle wells. The characteristic sinusoidal patterns from intersecting beds are also observed. The amplitude of the sinusoid is representative of the magnitude of the apparent dip. For reference, the processed image as it appears when the original aspect ratio is preserved has been plotted in the far right image track in Figure 2.

The density LWD instrument used to produce the images in this publication was specifically designed to run close to the centre of the borehole, even in horizontal wells. The main benefit is an even coverage of the full circumference of the wellbore. Devices that

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Figure 2: Imaging with LWD rotational density, shown in 8 and 16 sector configurations. The first image track shows the individual sector density traces from which the image is derived; the next track represents the same data interpolated, while the far right track shows the image in its correct aspect.

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sag on the low side of the hole typically exhibit darker larger stand-off on the high side of the hole.

The parameter imaged in Figure 2 is the compensated density. Purely from a measurement perspective, compensated density is desirable for its accuracy and for its relative immunity to borehole effect and artefacts. For imaging however, feature resolution is just as important if not more so than accuracy and immunity to borehole effects. In the following paragraphs, two types of improved density compensation schemes will be demonstrated. The first type enhances the benefits of using the short spaced density for thin bed analysis; the second type uses the difference between the long and short spaced densities for borehole geometry and break-out analysis.

IMAGE RESOLUTION OF LWD TOOLS The imaging resolution of a logging sensor depends first and foremost on its design, but also in many instances on the actual logging environment. Images coming from deep within the formation, away from the borehole wall are normally much less resolved than those from near the wall itself. Keeping a small stand-off between the sensor and the borehole wall helps high resolution imagers achieve their full sharpness potential.

The table below lists nominal pixel dimensions for various LWD imaging sensors.

Table 1: Comparison of LWD image tool pixel.

Natural gamma images are poorly resolved, but they are robust, repeatable and easy to understand. Past efforts to improve the resolution of natural gamma images have focused on increasing the number of sectors while reducing the angular width of each sector through collimation. Such methods run into the limitation of low count rates per sector. A reduction in count rates causes high statistical noise that negates the improved resolution.

At the upper end of the resolution spectrum, electrical images acquired by StarTrak exhibit a high definition

with 0.25 x 0.25 pixels, ideal for fracture mapping and for very thin laminations analysis (Ritter 2004). StarTraks galvanic focused micro-resistivity sensor outperforms density and gamma for image sharpness. It is however limited to conductive mud applications.

Standard compensated density images have an intermediate estimated resolution of 3.5. This is quite suitable for structural analysis and for geological studies, but not adequate for some fine stratigraphy or fracture identification. A marked improvement seems possible by simply imaging the Near Detector density (also known as Short Spaced density). The smaller distance between the source and the near detector readily explains this finer resolution of 1.5. There is however a caveat: the short spaced density is particularly sensitive to hole rugosity and to stand-off between the sensor and the borehole wall. It is anticipated that simply imaging the short spaced density will produce an image that will reflect the formation fine density detail, but it will be at the price of high sensitivity to borehole geometry irregularity. An appropriate compensation scheme for minimizing the effect of borehole rugosity, while preserving the resolution of the near detector is developed in a subsequent section.

STANDARD COMPENSATED DENSITY IMAGES MAGNIFY THE APPARENT RUGOSITY OF THE WELLBORE Wellbore rugosity may be caused by the erratic behaviour of the BHA in some adverse drilling conditions. A bent motor used for steering is likely to generate corkscrew shaped holes with a pitch equal to the distance between the drill bit face and the mid-point on the near bit stabilizer. Small-scale hole spiralling is known to occur with rotary steerable systems, particularly when the bit cutting specifications are not matched to the steering head performance (Pastusek et Al, 2003), or when the reactivity of the closed loop system of the drilling apparatus results in cyclical corrections with a characteristic periodicity. Last but not least, spiralling is known to occur also with conventional rotary BHAs under certain drilling conditions.

Other causes of wellbore rugosity include the tectonic stress field around the formation or to the interaction with the drilling fluid. A large horizontal stress such as observed at the foothills of the Rockies or the Andes create an elliptical hole shape in vertical wells within minutes of drilling. Suboptimal drilling fluids are known to cause shale to swell and to slough.

The basic density measurement is inherently very sensitive to the magnitude of the stand-off between the face of the sensor and the formation. Any increase in

Imaging LWD Tool Nominal Pixel Size

Azimuthal Gamma 6

Azimuthal Density Compensated Density Near Detector Density

3.5 1.5

Resistivity (StarTrak) 0.25

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the stand-off due to shape irregularity results in a significant reduction of the density reading, with dark areas appearing on the image. Note that for petrophysical evaluation only the highest quality data from any given scan are selected to contribute to the density log. Special algorithms based on distance to the borehole wall (Minette, 1995) or to the low side (Evans et Al, 1995) perform that selection. For imaging however, the complete azimuthal scan is needed to produce a full circumference density map.

Small-scale spiralling is visually magnified by the standard compensated density image. A change in the stand-off in the order of a fraction of an inch introduces a change in the density image that is significantly more visible than the features related to the formation itself. In such cases the hole rugosity artefact dominates. In the image of Figure 3 for instance, borehole geometry effect practically masks the finer detail features of the formation.

By properly combining count rates from near and far detectors it is possible to infer at any given moment the distance from the face of the instrument to the actual borehole wall. This parameter computed at every depth and for every azimuth helps generate a highly resolved 3-D image of the borehole profile.

Figure 4 shows a typical borehole shape from small-scale spiralling, plotted at three different scales: The scale applied in the middle picture is commonly used in such representations. It severely skews the aspect ratio by compressing the depth dimension in relation to the radial dimension. In this particular case the length of the wellbore shown is 50 feet, while the inner hole diameter is only 8.5 inches. The aspect ratio is amplified by over 25:1, magnifying the hole spiralling and its visual impact.

Figure 4: Actual hole rugosity for the example of Figure 3. The computed magnitude shown between the arrows is in the order of 3mm.

Figure 3: Images from standard compensated density are very sensitive to hole condition; they suggest a much more pronounced spiralling than reality.


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The 3D representation by the upper plot of Figure 4 is scaled closer to reality with an aspect ratio amplification of only 8:1 between depth and radius. Hole spiralling seems much less pronounced. The lowermost picture in Figure 4 is plotted with a scale that preserves the aspect ratio between depth and radius. The true borehole deformation is barely visible and seems much more reasonable than what was suggested by the rugosity in the image of Figure 3. The typical change in hole diameter in the subinterval of Figure 4 is only on the order of 3 mm.

Density sensor response functions were used to verify and to expand upon the results shown above. In the computer simulation summarized in Figure 5, a spiralled borehole was modelled by cutting three circular grooves around the circumference of the wellbore, one every 40 inches. The respective depths of the grooves increased progressively from 1/16 to 1/8 and then to 3/16.

Formation density was assumed constant throughout at 2.6 g/cc. The responses of the long spaced detector and of the short spaced detector were computed and then combined according to the standard density compensation algorithm. The computer simulated density image of Figure 5 confirmed the magnitude of the observed artefacts of Figures 3 and 4.

In the next section a method is described to deal with this type of image artefact induced by the rugosity of the borehole.

Sensitivity of density images to borehole shape is a double edged sword. On one hand it can be detrimental to geological detail as it magnifies hole irregularity over true formation features. On the other hand, it presents a unique opportunity for detailed hole shape analysis for drilling and geomechanics related applications. A highly resolved mapping of the borehole shape provides

Figure 5: The micro-rugosity effects on images from standard density are confirmed by modelling. Y


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an insight to drilling problems, hole stability issues and anisotropy of the stress field from the surrounding formations.

Processing of images from density is therefore carried out along two complementary avenues:

- Produce a geological image that is more immune to borehole rugosity than the standard compensated density. Enhance the bed resolution of the image while maintaining its relative immunity to borehole rugosity.

- Extract the highly resolved stand-off and borehole geometry information from the difference between the long and short spaced densities and use it to map the shape of the borehole and the tool position in the well, to identify early borehole break-outs and to study stress anisotropy.

A METHOD FOR IMPROVED DENSITY IMAGING TOLERANT OF BOREHOLE RUGOSITY The density response function simulating the response to grooves in the borehole wall (Figure 5) was extended to simulate additional cases. It predicted one additional important artefact associated with the standard density processing. At sharp boundaries where the intrinsic density undergoes a large and rapid change, there is evidence of potential artefacts and smearing (feature resolution degradation) at boundaries.

There is a common origin for anomalous responses from step changes in formation density and from rugosity and grooves in the borehole wall: It is the mismatch between the spatial response of the short spaced detector and that of the long spaced detector. Standard density processing is optimized for infinitely

Figure 6: Depth and resolution matching reduces the sensitivity of density images to borehole rugosity.


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thick beds. The compensation for mudcake and standoff by the short spaced detector works well when the formation and mud density are constant. However when step changes occur the transitional responses of the two detectors respectively take place at different depths and with a different resolution.

A new algorithm combining depth matching and resolution matching of the two detectors responses brings a significant improvement to the quality of the image. The rugosity effect is quite reduced and the apparent resolution of bed boundary features increased.

The new algorithm was first tested on the synthetic data from the density sensor response function modelling of Figure 5. The physical configuration simulates the sinusoidal variation of the spatial position of the borehole seen in small-scale spiralling. Test results are shown in Figure 6. The proposed algorithm eliminates the rugosity effect on the model. The image reflects the constancy of the formation density without any significant perturbation from the hole shape anomalies.

The algorithm was then tested on a thin bed model to verify its effectiveness at reducing boundary resolution artefacts. In the theoretical configuration of Figure 7 the bed resolution is somewhat improved, although not nearly as well as what could theoretically be obtained from the short-spaced sensor alone.

The algorithm was then applied to the real case of borehole spiralling described earlier in Figure 4. Unlike the modelled configuration the real case had no pre-

identified answer. One could assume however that regular periodic striations were induced by drilling, while the characteristic sinusoidal patterns were representative of true geological features such as thin beds. This observation was not used as part of the algorithm, but merely to assess the validity of the results. As seen in Figure 8, the depth and resolution matching algorithm successfully removed the striations due to borehole shape irregularities.

Finally, the proposed algorithm was applied to a layering of thin beds where overshoots had been observed. The sinusoidal white band in the original image at depth xx05, displayed on the left hand side of Figure 9 appeared unrealistic and similar to those seen in the computer model of Figure 7.

Once more the new algorithm removed the unwanted halo and restored the image to a more likely representation of the formation. Combining depth and resolution matching of the detectors response seemed effective at dealing with both borehole rugosity and step changes in density. However, while subduing the artefact the proposed algorithm did cause an apparent degradation in resolution.

The question that came naturally to mind was whether an improved algorithm could be devised that would enhance the resolution of the image down to the near detector resolution level while maintaining an immunity to the artefacts cited above.

Figure 7: Depth and resolution matching reduces the smearing in the imaging of sharp boundaries.

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Figure 8: Depth and resolution matching reduces the sensitivity to hole rugosity and small-scale spiralling, as applied to a real case example.

Figure 9: Reduction of the halo (at xx04) through the use of depth and resolution matching, though showing an apparent reduction in resolution.


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SHARP DENSITY IMAGES FROM THE SHORT SPACED MEASUREMENT FOR THIN BED ANALYSIS Signal from the short spaced detector was expected to naturally yield a sharper image than the standard density. But the short spaced log is also known to be highly dependent on stand-off. Consequently the images were also expected to exhibit an increased sensitivity to borehole rugosity

This was indeed verified in Figure 10. The image from the raw, uncorrected short spaced detector did exhibit a sharper response, but with a higher sensitivity to borehole shape. The dark side-bands on the short spaced density image of Figure 10 occur precisely on the high side, when the face of the detector is furthest from the borehole wall.

The density sensor subject of the study was a full bore sensor. The image obtained from standard density processing combining long spaced and short spaced detectors is seen on the left hand side of Figure 10. It

showed no side-bands. This was proof that the combination of full bore sensor and standard density processing was capable of fully compensating for the mud effect all around the circumference of the wellbore. Less capable sensors tend to produce dark side-bands caused by the large stand-off on the high side of the image. In the present case, side-bands were observed only for the uncompensated short spaced measurment as it has no correction for stand-off or mudcake effects.

The new algorithm was further enhanced to take advantage of the fine resolution of the raw short spaced measurement. An option was added to effectively correct that measurement for stand-off. The ensuing image resolution is closer to that of the raw short spaced detector but the stand-off effect is indeed significantly reduced. This remarkable result is best seen on Figure 10. Most of the features of the image from the raw short spaced image are retained in the compensated short spaced image, but the dark side-bands indicative of sensitivity to hole shape have practically disappeared.

Figure 10: Comparison of Standard Density, short spaced measurement (sharp but sensitive to standoff), and short spaced depth and resolution super-matched applied to a real case example. Y


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BOREHOLE FEATURES FROM DENSITY The high sensitivity of the density measurement to the distance between sensor and borehole wall can in fact be turned from a disadvantage into a benefit. In the above sections of this document, effort was focused at compensating for the stand-off effect. In this section, the focus is to transform the difference between the long and short spaced sensor measurements into an actual map of the borehole shape.

Simply stated, the distance between the sensors and the borehole wall (stand-off) can be expressed as a function of the difference between the long and short spaced densities. A small difference means a small stand-off, and a large difference means a large stand-off. This is true up to a point where the formation is out of reach of both long and short spaced measurements. In this case, both sensors start reading the density of the drilling fluid and their difference goes to zero.

By mapping the stand-off around the circumference of the wellbore a 2-D representation and a 3-D representation of the borehole shape can be derived, under some simplifying assumptions. Figure 11 shows small-scale spiralling of the wellbore, with the borehole radius multiplied by a factor of 10 to illustrate the irregularities.

This ability to image minute changes in hole size with azimuthal sensitivity is particularly useful in case of a formation with a high stress anisotropy. Such anisotropic

behaviour is commonly encountered for instance in the foothills of mountain ranges like the Rockies or the Andes. Determining the magnitude and the direction of the borehole breakout (Figure 12) provides valuable information to the drilling engineer and to the mud engineer.

The density instrument which is the subject of this publication possesses in addition an azimuthal acoustic stand-off that can also be used to produce a 3-D image of the borehole to directly confirm the shape inferred from the magnitude of the density compensation.

CONCLUSION AND SUMMARY Density images provide valuable information to study the geology of the subsurface, to geosteer the well and to visualise detailed borehole geometry for optimum drilling. Three different processing methods were presented that bring out the information for the different applications respectively. The first method reduces artefacts on the geological image created by borehole shape irregularities. The second method enhances the resolution of the geological image while tolerating some level of borehole rugosity and the third method provides detailed geometrical description of the borehole by amplifying the sensitivity to stand-off. Applications of the first two include structural studies and improved dip determination. The third one is particularly useful for the geomechanical study of the formation and for better selection of critical drilling parameters.

Figure 11: Density compensation, very sensitive to stand-off produces highly magnified 3-D images of hole irregularity.


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REFERENCES MINETTE, D., 1992. Method for analyzing formation data from a formation evaluation MWD logging tool U.S. Patent 5,091,644. February 25, 1992.

RITTER, R.N., CHEMALI, R., LOFTS, J., GOREK, M., FULDA, C., MORRIS, S., KRUEGER, V., 2004. High resolution visualization of near wellbore geology using while-drilling electrical images SPWLA 45th Annual Logging Symposium. Later published in Petrophysics, 46, 85-95.

PASTUSEK, P., BRAKIN, V., 2003. A model for borehole oscillations. SPE Annual Technical Conference and Exhibition, Paper 84448. October 5-8, 2003, Denver Colorado.

MINETTE, D., 1995. Method for analyzing formation data from a formation evaluation measurement-while-drilling logging tool U.S. Patent 5,397,893. March 14, 1995.

EVANS, M., BEST, D., HOLENKA, J., KURKOSKI, P., SLOAN, W., 1995. Improved Formation Evaluation Using Azimuthal Porosity Data While Drilling. SPE Annual Technical Conference and Exhibition, Paper 30546. October 22-25, Dallas.

ACKNOWLEDGEMENTS The authors wish to thank the management of Total and Baker Hughes for permission to publish this paper.

ABOUT THE AUTHORS Nicolas Meyer received a geology degree from the cole Nationale Suprieure de Gologie in Nancy (France). He has over 24 years experience in subsurface and Operation Geology with Elf and Total. For the last 10 years, he has been mainly involved in the LWD and geosteering know how development and training. He is currently working within the Complex Wells team in Totals HQ in Paris.

Steve Holehouse received a Geology degree from the University of Sheffield, UK. He has over 25 years experience in Geological Operations and Exploration Project Management and currently is the Complex Well Co-ordinator in Total's HQ organisation, based in Paris.

Andrew Kirkwood holds a doctorate in Chemical Physics from the University of Toronto. Over the past 10 years he has led numerous LWD efforts, spanning business development to interpretation development. He is currently leading a Knowledge Management initiative for Baker Atlas and INTEQ.

Derick Zurcher holds a degree in Petroleum Geology and Geophysics from the NCPGG, Adelaide. His recent experience includes working as a LWD Engineer and field testing latest generation nuclear tools. He is currently a Petrophysicist at Baker Hughes INTEQ, with specific focus on LWD imaging applications.

Roland Chemali received his engineering degree from the cole Polytechnique of Paris. He has co-authored over 30 papers and patents in electrical and acoustic logging. He is currently Product Line Manager for Emerging Technologies at Baker Hughes INTEQ in Houston.

Jeremy (Jez) Lofts received his PhD from Leicester, UK in 1993 and he is a Chartered Geologist. He has worked as an image interpretation specialist and he lectures externally/internally on the subjects of Borehole Image Interpretation. Jez is author of +25 papers on geological and petrophysical oilfield applications. He is currently the Product Line Director for LWD and Formation Evaluation at Baker Hughes INTEQ.

Geoff Page holds a physics degree from the Royal college of Science in London. With 25 years experience he is the Region Petrophysicist for Baker Atlas and INTEQ. He is the author of numerous technical papers and a past President of Aberdeen SPWLA chapter.

Figure 12: A 3-D image of the borehole derived from density compensation gives a clear indication of borehole breakout.

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