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7/28/2019 G a s D e t e c t i o n i n D e e p l y I n v a d e d

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54C h i n a 1 9 9 7 W e l l E v a l u a t i o n C o n f e r e n c e

4 . 4 . 3 G a s D e t e c t i o n i n D e e p l y I n v a d e d

S h a l y S a n d s a n d V o l c a n i c R e s e r v o i r s

V i c e - c h i e f E n g i n e e r , S e n i o r P e t r o p h y s i c i s t , F u Y o u s h e n g W e l l L o g g i n g C o m p a n y o f D a q i n g P e t r o l e u m A d m i n i s t r a t i v e B u r e a u , D a q i n g

L o g A n a l y s t s , W a n g D e f u a n d Z h u Y o u q i n g

I n t e r p r e t a t i o n a n d C o m p u t i n g C e n t e r , W e l l L o g g i n g C o m p a n y o f D a q i n g P e t r o l e u m A d m i n i s t r a t i v e B u r e a u , D a q i n g

Introduction

The appraisal well discussed in this paper is located in the

eastern fault block of the Wangjiatun structure which is

within the Xujiaweizi graben, in the south-east part of

Songliao Basin. The main target for this well is the

Denglongku Formation, a unit which includes laminated

sandstones and sandstone lenses. The porosity of

reservoirs in the area ranges from 6 to 11% and per-

meability from 1 to 5 md. All of the hydrocarbon-bearing

reservoirs in this group are dominated by gas.

Accurate evaluation of the Denglongku gas-bearing sands

is challenging. The sands are shaly, which masks the gas

effect seen on resistivity and neutron logs. Furthermore,

invasion by drilling fluids is usually very deep, which com-

plicates the evaluation even further. The Daqing Well

Logging Company has found that conventional logging

technology cannot provide accurate or reliable saturation

information under these conditions. As a result, all poten-

tial reservoir intervals need to be tested. This is anexpensive and time-consuming process: the reservoir

bodies are lenses, so continuity of petrophysical char-

acteristics cannot be inferred within the field.

A fractured, gas-bearing, volcanic reservoir has also been

encountered below the Denglongku sands.

Logging program

The logging program for this delineation well was

designed to produce a data set which was highly sensitive

to gas, even in the presence of shale beds and deep

invasion.

The Array Induction Imager Tool (AIT*) provides a deep

resistivity investigation to a depth of 90 inches (2.3 m),

which is 50% deeper than conventional induction tech-

niques. The five resistivity curves from the AIT, all plotted

with the same vertical resolution (30 cm), have between

four and six times better resolution than conventional

induction results, and with well-controlled depth of

investigation (10, 20, 30, 60 and 90 inches), allow a more

accurate determination of the undisturbed formation

resistivity Rt. This is very important for improving the

accuracy of gas saturation assessment.

Apart from conventional electron dens ity and ca liper

information, the Integrated Porosity Lithology (IPL*) toolprovides:

a neutron porosity that is less affected by shales than

conventional neutron porosities

a capture cross-section of the formation

natural gamma-ray spectroscopy curves such as

uranium-free gamma-ray activity and natural activities

due to thorium, uranium and potassium compounds.


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Table 1 Endpoint values assigned to each input log for

materials included in the model

Rxo

APLC

NRHB 0.15

Rt

0.21

0

GR (upper zone)

GR (lower zone)

0

0.15

0.21

0

4

0

1.004

1

0

0

0.992

1

0

22.2

0

2.626

0.01

58

11.1

35

2.6

0

160

16

160

2.68

0.01

60

14

60

2.68

0.25

3

3

150

31

150

2.59

0.01

111

15.7

80

2.65

0.015

5

8

5

SIGF

Undisturbed

gas

UGAS XGAS UWAT XWATTuff

Invaded

zone water

Undisturbed

water

Invaded

zone gas Igneous

fragmentsLava Clay Feldspar Quartz


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Using a neutron porosity with a reduced shale effect while

retaining the full effects of formation porosity and gas

saturation provides an added sensitivity to gas saturation.

Moreover, the formation capture cross-section is highly

sensitive to shale volume and gas saturation and so pro-

vides an additional evaluation input directly related to gas.

The combination of gamma-ray spectroscopy data with

formation capture cross-section is a major improvement

over conventional total gamma-ray measurements and

helps to improve shale volume evaluation. This has

important repercussions for the evaluation of effective

porosity, hydrocarbon saturation, permeability and

irreducible water volume, all of which are important

factors for predicting production performance.

The Fullbore Formation MicroImager (FMI*) tool was also

used in this logging program. Aside from its normal

geological and stratigraphic value, use of the tools high

vert ical resolution average resist iv ity curve helped toassess true bed thickness and enhanced the vertical resol-

ution of other logs. These features are described in more

detail in Section 4.4.2.

ELANPlus processing

The Elemental Log Analysis (ELANPlus*) processor is a

nonlinear, least squares minimization routine that

attempts to minimize the error between observed logs and

reconstructed logs by following a specific formation

model. The quality of the final interpreted results depends

on both the quality and choice of the input log data andthe quality of the evaluation model input to the processor.

Formation model

The formation model is usually defined by a log analyst

after studying raw log response, external information such

as expected lithology and drilling returns analysis and

description. This is a mathematical process, so the com-

plexity of the model (e.g. the number of unknowns) is

linked to the number of independent input logs and con-

straints available.

Two separate models were used to describe the formation

in this well. The main model was a shaly sand model

including parameters for the rock matrix, clay and clay-

bound water, quartz, feldspars, igneous fragments, and

(for the pore space) gas and water. The second model (an

igneous rock model) was developed for the lower section

of the well. This included parameters for clay and clay-

bound water, tuff and lava for the rock matrix, and (for the

pore space) gas and water.

The Indonesia saturation equation, which usually provides

good results in the shaly sand condition encountered in

Chinas oil fields, was chosen to derive saturation from the

resistivity data.

Input log data

The input log data consisted of invasion-corrected deep

and shallow induction readings (AORT and AORX) from

the AIT tool for evaluating Sw and Sxo. The IPL tool was

used for lithology evaluation, and the data it provided

included epithermal neutron porosity (limestone corrected

APLC), enhanced vert ical resolution formation electron

density (NRHB), uranium-free natural gamma-ray activity

(HCGR) and the formation thermal neutron capture cross-

section (SIGF).

Main evaluation parameters

Saturation evaluation (Indonesiasaturation equation model)

The saturation exponent and cementation factors were

assigned their default value of m=n=2. The formation

factor multiplier A was also set at its default value of 1.

Mud filtrate salinity was set at 3.3 parts per thousand

(ppk) on the basis of the wellsite mud filtrate measure-

ment. Formation water salinity was set at 3.5 ppk, a typicalvalue for this area.

The use of the Indonesia saturation equation and default

values of 2 for the saturation exponent and cementation

factors are well-suited to the shaly sand model. In the

fractured volcanic lithology, a variable m model would

perhaps be more appropriate for saturation estimation

as m is likely to fall below 2 in fractured intervals. This

modification was not attempted because there were

other, even more important, problems to be considered,

such as shale content evaluation and effective porosity

determination. Unfortunately, no core data were avail-

able to attempt a fine-tuning calibration of the volcanicrock model.


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*

Figure 1A short section of

the final well evaluation plot

for the appraisal well. Note

the relatively high

permeability in the cleanest

reservoir zone and large

invasion-related

displacement of gas


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Lithology and porosity evaluation

Endpoint values are assigned to each input log for each

material volume included in the model . These are

summarized in Table 1.

The clay-bound water volume was set at 15.6% of the dry

clay volume.

Postprocessing

Once the lithology, porosity and hydrocarbon saturation

are well defined, a postprocessing module uses these

results to compute other parameters linked to the pro-

ducibility of the reservoirs under evaluation. Effective

porosity and lithology are used to derive an estimate of

reservoir permeabil i ty to brine (K in t, or Intrinsic

Permeability). A volume of irreducible, capillary-bound,

water (Vwi), and an irreducible water saturation (Swi), are

further derived from knowledge of the porosity, per-meability and hydrocarbon saturation of the formation,

using the well-established Timur relationship.

The permeability factors associated with shaly sand

minerals are well defined. Providing that the IPL tool is

used to obtain an accurate estimate of sand, feldspars and

shale, a reasonable estimate of permeability can be made.

However, with volcanic fragments in shaly sands, as well

as for the igneous rock model, permeability factors are less

well defined. As a result, and particularly for the igneousrock model, the permeability and irreducible water

saturation estimates may be erroneous, especially since

they are made without the benefit of core calibration

points. The Combinable Magnetic Resonance (CMR*) tool

provides a quasi-direct measurement of permeability and a

direct measurement of irreducible water volume, and its

use is strongly recommended for future operations.

In the following list of permeability factors attributed to

the different minerals, a factor greater than zero indicates a

material whose presence enhances reservoir permeability,

and a value lower than zero indicates a material whose

presence decreases permeability.

Figure 2a Typical Group A

gas-bearing reservoir

Figure 2b Group A gas-

bearing reservoir with low

natural permeability


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Figure 3a Typical upper

Group B reservoir


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Clay 6.0

Igneous fragments 3.5

Tuff 1.0

Lava 0.5

Feldspar 1.0

Quartz 0.1

Well evaluation plot description

Figure 1 shows a short section of the final well evaluation

plot, including the scaling insert. The presentation is

divided into four log tracks and a depth track at the

extreme left.

From right to left, track IV displays formation volume

analysis, including assessments of both rock- and fluid-filled

volumes. Analysis of the fluid-fi lled volumes is describedbelow in the discussion of track III. Rock volumes include

dry clay, and the clay-bound water. Siliciclastic reservoir

rocks contain quartz, feldspar and igneous fragments.

Volcanic rocks including tuff and lava are also represented.

The effective formation porosity parameter PIGE separates

rock volumes from fluid volumes.

Track III features a detailed analysis of the fluid volumes.

This is repeated from track IV, but provides a more sensi-

tive (and therefore easier to read) effective porosity scale,

from 50 to 0%. Water-filled volumes are shown in blue

and gas volumes in red. The ELANPlus formation water

saturation computed from the AIT-derived Rt parameter

splits the effective porosity volume into those two com-

ponents. The gas saturation of the invaded zone is com-

puted using the Rxo reading derived from the AIT device.

This parameter allows the separation of total gas into

nonmoved gas, present very close to the borehole wall

(X_Zone Gas), shown in red, and deeper gas that has been

flushed away by invasion (Moved_Gas), shown in orange.

The reservoir displayed in Figure 1 shows massive gas dis-

placement by invasion; in other words, gas mobility in this

reservoir is excellent. The formation water volume is also

split into two separate volumes, using the irreducible

water volume parameter computed by the ELANPlus post-processing module . These are the capil lary-bound

irreducible water volume (light blue) and the producible

water volume (dark blue). Where significant volumes of

producible water are shown, water production (in addition

to any gas) is expected. Where only capillary-bound water

is present, no water should be produced.

On the right side of track III, log analyst reservoir interpre-

tation flags are displayed. These flags are a log analysts

interpretation of the raw log measurements, the ELANPlus

evaluation and any external data available. It is a pre-

diction of the fluids that would be produced if the

reservoir analysed was open to production.

The flag coding for all of the logs in this paper are as

follows:

Red with g Dry-gas production

Pink with tg Tight sand, dry gas production (little)

Pink with gcw Gas reservoir with water production

White with wcg Water reservoir containing some gas

Brown with d Dry zone, no production expected.

Whenever possible, actual test results are compared to the

predictions made on the basis of the log data. The pre-dictions were made before test results became available.

Track II contains the water saturation results on a scale

(left to right) of 1 to 0. The area between the pure water

line (Sw=1) and actual formation saturation is pink and

represents zones where gas is present.

Track I displays the intrinsic or brine permeability of the

formation. Its scaling is logarithmic and covers a range of

val ues from 10 darcies to 0.1 md. Perme abl e reservoir

intervals are highlighted in yellow.

Well evaluation

After integrating the ELANPlus results, all logs and other

available information, it is possible to divide the entire

survey interval into five separate formation groups. The

classification is based on lithological and geological par-

ameters rather than reservoir saturation characteristics,

although in most cases, water saturation characteristics are

closely linked to the lithological groups. These groups will

be discussed in order from top to bottom of the sequence.

Group A (23422620m)

The reservoirs in this group are gas-bearing. There is very

little free water in this section, with all free pore space being

gas-saturated. Reservoirs where porosity and permeability

are high enough should produce gas with little or no water.

Figures 1, 2a and 2b show reservoirs typical to this group.

The reservoirs in Figures 2a and 2b have been tested and

the results confirm the log analysts producibility estimates

derived from log data and ELANPlus evaluation.


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Figure 3b Group B transition

zone reservoir


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A comparison of reservoir characteristics in Figures 1 and

2b provides some interesting information. Both reservoirs

contain large volumes of gas. The reservoir in Figure 1

shows a relatively high permeability (about 10 md) in the

cleanest reservoir section, and a large invasion-related dis-

placement of gas. In contrast, the reservoir in Figure 2b

shows a much reduced permeability (averaging only0.5 md) and virtually no gas displacement. The low per-

meability characteristics of reservoir 2b were confirmed

by test results. Gas production in this reservoir increased

by a factor of 10 between tests performed before and after

fracing. The reservoir in Figure 1 is likely to produce

much more gas without stimulation than the reservoir of

Figure 2b was producing before its flow characteristics

were modified by the fracing program.

Group B (26202811 m)

Reservoirs in this group appear to be part of a transitionzone, from gas to water. Two typical reservoirs sections are

shown in Figures 3a and 3b, clearly illustrating how the

amount of free water increases with depth into the

transition zone. Test results confirm the transition zone

hypothesis. A mixture of gas and water is produced at the

top of the transition zone but only water is produced

lower down.

Although the general saturation trend in this group can be

characterized as a transition zone, careful analysis should

be made of saturation versus permeability. For example,

the reservoir between 2689 and 2694 m has low water

saturation in low permeability streaks and high watersaturation in high permeability streaks, and so would be

expected to produce water: this was confirmed by testing.

In contrast, the reservoir between 2695 and 2698m shows

low water saturation in the most permeable interval. It is,

therefore, expected to produce gas, even though it is below

a water-producing interval. Although the reservoirs are not

particularly thinly bedded, their permeabil i ty and

saturation characteristics are thinly heterogeneous and this

is where the enhanced vertical resolution and careful

depth matching afforded by the FMI-derived resistivity be-come important for proper reservoir evaluation.

The transition from gas to water is complete at 2770 m, and

only water is present below this level. This water-bearing

zone (down to 2811 m) is assigned to Group B because the

general electrofacies of the raw logs is typical of the group.

Group C (28112933 m)

All of the potential reservoirs in this zone are water-bearing.

Few of them have sufficiently high porosity and per-

meability values for water production. Most are dry in the

sense that all of the water contained in the pore space is

capillary-bound. In Figure 4, only the lower section of the

upper reservoir contains free water. All of the other reservoir

intervals contain only capillary-bound or irreducible water,

indicating that there will be no fluid production.

Group D (29333074 m)

Reservoirs in this group are all composed of fractured,

porous, volcanic rocks. In unconventional reservoirs such

as these, the response of logging devices is not as

accurately defined as it would be in siliciclastic and

carbonate reservoirs. Without core calibration of logresponse to the particular volcanic rock mixture in the

area, it is very difficult to evaluate the shale volume and

the effective porosity of the formation accurately. In

Figure 4 Typical water-bearing

reservoirs (Group C)


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Figure 5 Typical gas-bearing

fractured volcanic reservoirs

(Group D)


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addition, the exponent m of the saturation equation

should probably be set to a value lower than 2 due to the

fractured nature of the reservoirs. An additional problem is

that the permeability factors for the volcanic constituents

of the reservoir are not well known either. As a result of

these uncertainties, the permeability derivation can only be

an approximation, so evaluation of the irreducible watervolume is also approximate. The accuracy of the ELANPlus

evaluation can be adversely affected by all of these poten-

tial sources of error.

Figure 5 shows that the match between predicted results

and actual test results in the igneous section of the well is

less accurate than in the siliciclastic reservoir section. The

ELANPlus evaluation predicts that gas will be produced

with some water, but test results indicate dry gas

production. This discrepancy could be due, in part, to the

potential sources of evaluation errors discussed above

and/or to the fact that short-duration well tests are not

always fully representative of long-term production. In this

case , when the reservoir was put into long-term

production, some water was produced.

Group E (3074 m to TD)

Below 3074 m the log response defines an electrofacies

closely related to the electrofacies of the shales above the

igneous reservoir section. It appears that the bottom of the

volcanic sequence has been reached at 3074 m and that

the shale unit below has no hydrocarbon reservoirs. The

upper 6 m of this shale are altered by deposition of the

overlying igneous section. Alteration is possibly due totemperature-induced effects and to the explosive inclusion

of volcanic debris.

Conclusion

An imaging technology logging program carefully adapted

to specific formation evaluation needs has successfully pre-

dicted production characteristics in all of the reservoirs.

Evaluation forecasts have been verified by extensive testing

and by production results. The key elements for this

successful evaluation were contributed by a relatively

restricted logging program using AIT, IPL and FMI tools.

The AIT tool combination of a deep resistivity reading with

four shallower resistivities provides a good description of

the formations invasion profile and, therefore, a robust,

reliable and small invasion correction, producing an

excellent estimate of virgin zone resistivity. This is an

essential element for accurate evaluation of the reservoirs

hydrocarbon saturation.

The IPL tools combination of formation density, neutron

porosity unaffected by shale density nor thermal neutron

capture characteristics, and elemental natural gamma-ray

spectroscopy, provides a very accurate l i thology

description in a complex formation. This accurate

description delivers three parameters essential to a

reservoir production forecast: effective porosity, per-

meability and irreducible saturation or capillary-bound

water volume.

The FMI tool provides fine vertical resolution and true bed

thicknesses. In addition to its usual geological uses, the

FMI also provides the means to improve vertical resolution

of other logs and detailed depth correlation. Both of theseare essential functions and contribute to a better under-

standing of reservoirs with thinly-bedded permeability and

saturation heterogeneities.

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