INTEGRATION OF IMAGE LOGS IN BROWN FIELD MANAGEMENT · confidence on borehole images. The...

SPWLA-INDIA 3rd Annual Logging Symposium, Mumbai, India Nov 25-26, 2011

INTEGRATION OF IMAGE LOGS IN BROWN FIELD MANAGEMENT

Chandramani Shrivastva1, Khalifa Muslem

2, Sajith Girinathan

3, Benamer Djamila

3,

Koushik Sikdar4, Sarvagya Parashar

4

1 Schlumberger Oman & UAE; 2 Schlumberger Oman; 3 Schlumberger UAE; 4 Schlumberger India

ABSTRACT

Petrophysical applications of borehole images have long been established in the exploration and development of

hydrocarbon reservoirs, apart from the more obvious geological applications. The heterogeneity indices derived

from image logs in both clastic and carbonate reservoirs are used extensively for the infill wells to optimize

production with intelligent completions. Vuggy porosity, fracture porosity, and aperture computations have

contributed to static modeling of the reservoirs.

Image logs can be used effectively in Brownfield management as well, delivering meaningful input to improved oil

recovery (IOR) and enhanced oil recovery (EOR) processes. Water-injection programs need detailed insight of

geological complexities for better efficiency. The sedimentary structures and diagenetic imprints, which are nicely

captured on the borehole images, control the preferred flow directions of the waterflood and play an important role

in flood efficiency depending on the location of the injector well. Such features along with any fractures must be

taken into consideration when planning the location of injectors. Similarly, steamflooding for heavy oil production

also can capitalize on knowledge of fractures and sedimentary features. Polymer flooding for EOR, using the log-

inject-log methodology based on in situ evaluation also relies on using borehole images to understand flood

development and compare after-injection flooding with simulation results.

Brownfield management also requires regular updating of the reservoir model, with more data streaming into the

process. Successful well placement must take into account the stress regime in performing hydorfracturing, and here

borehole images play an important role. A successful stimulation job incorporates a lot of input from borehole

imaging logs, not only to understand the stress regime, but also to understand differential diagenesis, which

determines reservoir properties that control optimal recovery. Stimulation by acid or a frac pad must ensure that it

does not connect the well to any high-permeability streaks or fractures, which could significantly increase the water-

cut in production. This is a concern in Brownfield management, which also aims to arrest declining hydrocarbon

production over time.

Different methodologies for brown field development can be augmented with integrated applications of image logs

for optimizing the efficiency of non primary recovery processes. This paper introduces and summarizes how this

approach to successful brown field management honors geological complexity.

INTRODUCTION

Borehole imaging has been an integral part of logging programs for exploration well since long due to its application

in deciphering the geological complexities. The sub-seismic faults and fractures were always interpreted with

confidence on borehole images. The sedimentological applications of the image logs have been in place since the

dipmeter days as well. The famous red, green and blue patterns of interpreting the dipmeter data was applied in

understanding not only the structures, but also the depositional environments (Figure 1). With the advent of borehole

images (Figure 2), textural analysis was added to the geologist’s interpretation and gradually it led to the

development of petrophysical application of borehole images. Secondary porosity analysis, permeability estimation,

fracture analysis and Reservoir Rock typing are some of the largely used petrophysical applications based on the

high resolution image log data. Exploration geologists integrate the image logs with core and seismic to interpret the

sedimentary architecture (Shrivastva et al., 2008).


Figure 1: Example of dipmeter interpretation with dip trends colored in red, green and blue

Figure 2: 2-D unwrapped presentations of Borehole micro resistivity image -captured features with the help of sine

waves

The development wells in many carbonate fields have taken advantage of the textural details and heterogeneity to

optimize the completions, with the help of swell packers and blinds; isolating the zones which could be potential

trouble makers in the near future (Shrivastva et al., 2009). The understanding of fracture distribution and their

physical attributes like density, porosity and aperture have long been extensively used in many studies.

However, the application of image logs is not limited only to the exploration and development wells. The brown

field exploitation still can derive plethora of information from the image logs to help in optimal recovery. An

attempt has been made here to understand the application of borehole images in the secondary (Improved Oil

Recovery, IOR) or tertiary (Enhanced Recovery Processes, EOR) recovery processes in various phases.

Dynamic Image Static Image


IMAGE LOGS IN IOR/ EOR

The secondary and tertiary recovery processes aim at augmenting the reservoir pressure and altering the fluid

properties to facilitate flow of oil in to the well bore. Water flooding is an example of secondary recovery that

consists of planned injection well in pre-defined pattern to push the oil column up the producer well. The geological

understanding of sub-surface is very important to understand the existence of some natural preferred path of flow or

barrier to it. Image logs help a great deal in understanding the internal architecture of the sediments in clastic

reservoirs and existence of dissolution streaks in carbonate reservoirs. The presence of cross-beds in the sandstone

reservoirs (Figure 3) suggests the direction of least impedance to the fluid flow along it; whereas the fluid flow

across it would be difficult in comparison. A conceptual diagram in Figure 4 illustrates this. The injector in dark

blue shade would be more effective in its sweep to the producer well in red, compared to the injector in light blue

shade. The reason is: the water flood in dark blue injector would have to follow the easier path along the cross-bed

whereas the flood from the other injector would have to flow across the cross-beds as well.

Figure 3: Example of cross-bedded sands on core; with borehole images and dips (red tadpoles for cross-beds). The

image is a Static FMI normalized and oriented to North in a vertical well; and tadpoles are plotted from 0 to 90

magnitude.

Figure 4: Conceptual diagram with injectors (light blue & dark blue) and producer (red). The arrow shows

Paleocurrent direction.

Therefore, if the depositional architecture is properly understood, the injection program can benefit from this

concept. Jones et al. (1995) presented a study done by BP and Statoil Alliance that suggested that the sub-seismic

heterogeneities influence the water flood performance. In such experimental studies, the sedimentary structures and

their association with different units of depositional architecture tends to influence not only the flood patterns, but

also the flood efficiency. Feng et al. (2007) discussed the integration of geology in water injection optimization for a

complex heavy oil fluvial reservoir. Borehole images with their high resolution measurements capture the subtle


changes and in texture and sedimentary structures; thereby helping in the conceptualizing the preferred flow

directions in the sub-surface when subjected to water injection. Similarly, the steam injection can be aided with the

sedimentological model built with the help of image logs. In fact, there are many examples where the image log

studies have helped in water/ steam flooding of the reservoirs.

Otiocha et al. (2001) discussed how integration of image logs helped in proper water flooding in Oman. Yose et al.

(2006) provide a very detailed account of water flooding problem and their solution with meaningful input from core

and geological studies in UAE carbonates (Figure 5). Such depositional models are built with image logs

contribution, in absence of core data and provide a major control on the design of injectors. The injector in the

diagram in Figure 5 cannot support the producer left to it, due to the flow barrier across the perforation. This is due

to the heterogeneity in the carbonates produced by the clinoforms. Similarly, dissolution seams and fracture corridor

end up consuming the injection water many times, thereby hampering the water flood movement towards the

production well.

Figure 5: Injector support available to only one producer, in carbonates reservoir with clinoform. Adapted from

Yose et al (2006).

The steam injection program is also planned to exploit any existing fracture network to maximize the EOR. The

example below in Figure 6 shows Static image in a highly deviated well, oriented with respect to Top of Hole. The

thermal treatment of heavy oil reservoirs can exploit the existing fracture system, which can be mapped with

borehole images.

Figure 6: Almost vertical fractures in the steam injector project could contribute to optimal treatment of heavy oil.


IMAGE LOGS IN MICROPILOT

The MicroPilot concept is an offering for the EOR projects for quick screening of EOR process by altering

formation properties through the controlled injection of EOR-agents while measuring the recovery and/or

displacement behavior in-situ (Arora et al, 2010). The EOR fluid (with the polymers to be screened) is injected

downhole into the formation. The borehole images and saturation logs are recorded prior to and after the injection

and are compared for the changes in saturation. Borehole images are very important as they show the dimensions of

the swept zone (Figure 7). These measurements are run through reservoir simulation program to understand the

efficiency of the EOR polymers in the enhanced recovery of hydrocarbon on a field scale later on.

Figure 7: Schematic of Borehole image in MicroPilot, before and after injection

In the schematic (Figure 7), the left hand side reactance is a representation of borehole image, unwrapped in 2-D in

an oil bearing zone. The schematic is kept clean to illustrate the changes after the injection. The right hand side

reactance is the schematic of the borehole image after the injection. The red tiny point shows the injection point; the

blue shaded shape shows the conductive polymer flood and the yellow areola surrounding the polymer flood shows

the displaced oil rim.

IMAGE LOGS IN WELL-STIMULATION

Image logs play important role in the planning of well-stimulation by hydro-fracturing. The disturbance in the stress

regime manifests itself with drilling induced fractures or break-out on the borehole wall.

The borehole images with their high resolution measurements capture these signatures with their orientation. The

interpretation of this data provides information about the prevalent stresses direction (Figure 8). As a general

practice, the hydorfracturing is attempted to generate fractures in the direction of maximum horizontal stress

direction. At the same time, the frac length should honor the geological body orientation as well (Figure 9). A

fracture generated by stimulation might be planned wrongly running out of the sand body, thereby adding no value

for the extra frac pad it needed. The sand body geometry is interpreted with the help of the image logs in

conjunction with the core and seismic. A proper facies model can be developed and refined with the help of

borehole images (Shrivastva et al, 2008). The conceptual models thus developed in the sequence stratigraphic

framework provide clues about the possible reservoir distribution and their orientation.


Figure 8: Solving for stress regime with the help of induced fractures and break-out captured on borehole images.

(Parashar et al, 2010)

Figure 9: Fracture length vs. sand body orientation

The image interpretation also helps by identifying the diagenetic patterns and the tightness they add to the formation

which can make the hydro-fracturing difficult. The fault zones or the fracture corridor which have been cemented by

preferential fluid flow and subsequent precipitation render hardness to the tight reservoirs. The open faults or

fractures if connected by hydro-fracturing to the aquifer can cause an early water-cut which needs to be avoided.

Therefore, while planning the well-stimulation job the image logs become very critical in not only understanding the

stress regime, but also for the successful post-stimulation performance honoring the structural and sedimentological

complexities of the formation.

CONCLUSION

Borehole images have long been used in exploration and development wells. However, their application in brown

field management is also very varied and equally important. There are many examples in the water injection and

steam injection projects where the high resolution measurements of borehole images have been put to use to identify

sedimentary features and facies association. The IOR/ EOR projects honor the geological complexity and

heterogeneity of the sub surface for optimal recovery which can be deciphered with the help of borehole images.

Also, the well stimulation projects need to understand the structural and sedimentological elements of the sub-

surface in addition to the local stress regimes. The existing borehole images from such fields can be used for further

integration in brown field management; and more data can be acquired to compensate for the existing data gap for

borehole images. The integration of image logs plays a very important role, with other existing data and model in

efficient brown field management.


ACKNOWLEDGEMENT

Authors are grateful to the Schlumberger Middle East Asia management for their kind permission to present this

work. They also acknowledge different E&P companies across the Middle East Asia for the detailed discussions

about their brown field project practices.

REFERENCES

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