PROCEEDING, SEMINAR NASIONAL KEBUMIAN KE-10 … · proceeding, seminar nasional kebumian ke-10...

PROCEEDING, SEMINAR NASIONAL KEBUMIAN KE-10 PERAN PENELITIAN ILMU KEBUMIAN DALAM PEMBANGUNAN INFRASTRUKTUR DI INDONESIA

13 – 14 SEPTEMBER 2017; GRHA SABHA PRAMANA

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LITHO-SEISMIC CLASSIFICATION BASED ON ELASTIC ROCK PARAMETERS: CASE

STUDY – SOUTH PECIKO FIELD OFFSHORE MAHAKAM DELTA

Santika Satya Widita1

Didiek Budhy Prabowo2

Hilfan Khairy2 1 Geophysics Sub-department, Universitas Gadjah Mada

2 Total E&P Indonésie

ABSTRACT

Simultaneous seismic inversion was performed using the PSTM (Pre-stack Time Migration) data from

Peciko field which is located at offshore Mahakam PSC. The study concentrated in the Peciko Main

Zone area with 3km of burial depth. Five wells data which stand on the deltaic environment are used

for this study. Sedimentary rocks are mostly found on the study area. The main objective of this study

is to analyze the probability of facies in the study area based on lithology classification from elastic

rock parameters that gained from seismic inversion IP (P-Impedance) and PR (Poisson Ratio). Every

lithology such as sandstone, shale, or carbonate has its own different physical characteristic and can be

distinguished by using well data (density and sonic log) and seismic inversion data (IP and PR cubes).

Besides, cross-plot between IP and PR can also be the tools to differentiate fluid inside the formation,

such as gas- or water-bearing sand reservoir. The analysis of lithology classification which based on

the elastic rock parameter showed the information that can be used to more understand the lithology

probabilities in the study area, also geological model. Distinguish the lithologies in the study area is

quite challenging due to the depth of burial which is relatively deep and increase the compaction

among the rocks. It impacted the result of seismic inversion IP and PR which shown a less correlation

between those two elastic parameters therefore hardly to do the upscaling. In the other side, deltaic and

shelf environment have contrast lithology which made it as one of the challenges that need to be

resolved in this study. Cross-plot between IP and PR showed the lithology classification that fitted

with its real model then the Probability Density Function (PDF) is used as the statistical approach to

determine the facies’ probability. The result can be used for future well development.

Keywords: Simultaneous Seismic Inversion, Poisson Ratio, P-Impedance, PDF

1. Introduction

Seismic reservoir characteristic is started with feasibility study based on the log data

which done to understand if the elastic rock parameters (IP and PR) are able to differentiate

the lithology below the surface. Meanwhile, the inversion process can be used as the

estimation of elastic rock properties which derived from seismic data. The inversion result can

be transformed into the qualitative and quantitative of reservoir properties such as facies,

porosity, volume of clay, etc. The technique that will be used for transforming the inversion

result into the reservoir properties is called as litho-seismic classification and will be applied

on this study.

South Peciko is one of the Mahakam PSC which is discovered in 1983, with gas as its

product. It locates on the offshore of prolific Kutai basin at Mahakam delta, East Kalimantan,

Indonesia (Figure 1a). Upper Miocene fluvial and deltaic front environment are the

depositional environments of South Peciko field. Peciko Main Zone is deposited in the delta

front to pro-delta environment which consists of mouth-bar stacking (Lambert, 2003).

Simultaneous seismic inversion was performed using the PSTM (Pre-stack Time

Migration) angle stacks (Near, Mid, Far, Ultra-Far angle stack), resulted the Poisson Ratio

(PR) and Acoustic Impedance (IP) cube. Five wells were also used in this study to correlate

with seismic data (Figure 1b).

Cross-plot between IP and PR cubes could distinguish the lithologies due to its elastic

rocks characteristic. Burial of Peciko Main Zone is relatively deep, thus crossplot of elastic



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rock parameters (IP and PR) was quite difficult to separate the overlap facies which made this

issue as one of the challenges at this study.

The main objective is to analyze the probability of sandstone in the study area based

on lithology classification from elastic rock parameters that gained from seismic inversion IP

(P-Impedance) and PR (Poisson Ratio).

2. Methodology

The analysis was start with quality control of seismic data using four angle stacks (near,

mid, far, ultra-far stack) and compared each aligned, synthetics and residual seismic section.

Theoretically, if the aligned and synthetics seismic data are matched, the residual seismic data

will be shown a lower value. The analysis was done to the marker Beta until the end of well

trajectory.

Well data with density and sonic log (P wave velocity (Vp) and S wave velocity (Vs))

that was already filtered with low cut frequency (0 – 2 Hz) in order to remove the background

burial trend was used to generate the petro-elastic parameters IP and PR, which this process is

called as Detrending. These parameters based on the log scale will be crossed plot with color

coded lithologies sand, shale, and limestone to know the separation between each lithologies.

Good quality of sand will be shown by the low IP and PR, while limestone showed high IP

and PR but shale corresponded to high IP – low PR or/and low IP – high PR.

Log data was also filtered at the seismic scale with the seismic bandwidth frequency or

bandpass filter (6 – 30 Hz) and crossed plot with color code the upscaled lithology to match

the log data with seismic upscale. Then seismic inversion IP and PR cubes were also

detrended by using the bandpass filter frequency and crossed plot with color code the

upscaled lithology.

These cross-plots from log scale and seismic scale then compared to know the separation

between each lithologies. From the cross-plot result, Probability Density Function (PDF) map

could be generated as the operator for litho-seismic classification. The PDF map showed

probabilities of certain lithology in the IP and PR domain. The PDF operator is built based on

discriminant analysis called probabilistic Bayesian methodology which allows the operator to

characterize uncertainties by computing probability to discriminate each facies (Hand, 1981;

Choliq M. T., 2014)

The simplified workflow of the litho-seismic classification study is explained on the

Figure 2. The previous steps which include the removing the background burial trend at the

well log data and the inverted impedance cubes will be continued into the next four main

steps in the workflow.

The first step is crossplot between P-Impedance (IP) and Poisson Ratio (PR) generates

from the detrended elastic log with the color code is lithology sandstone, limestone, shale

or/and other facies. Theoretically, lithologies on the crossplot between two elastic rock

parameters should be able to be discriminated, but in this study, Figure 3 shows the inability

of IP and PR crossplot to discriminate of each lithologies. This case happened due to the well

data which could not determine the elastic rock parameters since there was only one well that

has the sonic log and density log (well B-1) while three other wells only have the predicted

sonic and density log (well N-14, P-1, and T-1)

Second step is crossplot between IP and PR generates from the inverted seismic cubes and

using the upscaled lithology as the color code. This crossplot is a tool to make sure the

separation between each lithologies is still valid. The lithology is upscaled into the seismic

resolution and inverted elastic rock parameter IP, PR are extracted along the well. On this

study, crossplot between inverted IP and PR showed a good separation between each

lithologies in seismic scale which could be observed on Figure 4.



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Litho-seismic classification is required an operator to obtain the reservoir property, which

one of the operators is called as Probability Density Function (PDF), and on the third step,

PDF map is generate as the operator for this study (Figure 5a). The probability of each

lithologies is showed on the PDF map by taking the account of density at each lithologies

which lies on the crossplot. Then this PDF map will be extrapolated therefor the possible

value of inverted IP, PR around the study area could be covered and presented in 3D volumes

or cubes (Figure 5b). The result of PDF map as the operation for litho-seismic classification.

The last step is computation of lithology probability cubes which requires the lithology

PDF operator on the inverted seismic cube. The result of this workflow is lithology

probability cube such as sandstone, limestone, or shale probability cube.

3. Result

When the lithology probability cube once made, quality control of wells, section and map

layer must be done. The good quality data is showed by the ability of each lithology to

discriminate, such as separation between sandstone and limestone or other lithology. Quality

control that has been done at the first was the extraction of the lithology probability along the

well and it will be compared with the lithology that recorded at wells (or called as Litho-log).

The analysis was made on each well data and has been checked on the well which do not have

any information about sonic and density log or refers to blind well (M-1). Result of B-1, N-14

and T-1 showed some good lithology probabilities even though some interval of depth

showed the questionable and doubtable result which can be seen at Figure 6 for well B-1,

Figure 7 for well N-14 and Figure 8 for well T-1. Blind well (M-1, Figure 9) also showed a

good result. Layer of thick sand could be distinguished while the thin sand layers were

hardly to detect for its probabilities. It happened due to the seismic resolution which could not

reach the thin layer. The term of questionable result was used for the lithology probability that

less from 50%, symbolized by orange color meanwhile the term of doubtable result was used

for the PDF lithology which not match with the litho-log, symbolized by red color. Well P-1

(Figure 10) was not used on the data processing due to the thick layer of limestone which

could disturb the lithology crossplot of elastic rock parameter IP and PR.

The second quality control has been done to lithology probability on the inverted IP and

PR cubes (Figure 11 until Figure 15). Probabilities of each lithology were compared with the

inverted IP and PR cube. The results showed a fair correlation between inverted IP, PR cube

and lithology probabilities. The quality control was not only analyzed the lithology

probability at the well but also around the well. The result of lithology probability of inverted

IP, PR on well B-1, N-14 and T-1 gave the information about the highest value of probability

which estimated from sub-surface data.

The last quality control was made on the map layer of sandstone probability and compared

with the inverted seismic cube from Mid angle stack. The map layer is divided into three

layers based on the seismic wiggle of its zone of interest at interval marker Beta – MF4.

The first layer (Figure 16) of elastic parameter IP, PR showed the high value of sandstone

probability at the north-east of the map layer, colored by green, meanwhile the mid-angle

stack first layer shows the high value of amplitude at the south-east, colored by red which

indicates the occurrences of rigid rocks on the area such as limestone. The high value of

sandstone probability could be delineated as channel structure that lies on the study area. This

channel also could be identified on the second layer (Figure 17) of sandstone probability from

elastic parameter IP, PR, while rigid rock starts to appear on the mid-angle stack map layer,

indicated by the high amplitude value. The third layer (Figure 18) gave a clarity between the

sandstone probability and amplitude at the mid-angle stack map. It means that some high



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value of sandstone probability lies between the rigid rocks that shows at the third layer of

mid-angle stack map, such as limestone. Analysis of the sandstone probability could be more

reliable with the addition of other supporting data in order to know the channel spreading.

4. Conclusions

Litho-seismic classification based on elastic rock parameter is an approach to understand

the lithology information such as sand probability. This approach is useful as subsurface

interpretation and as a guide to map the reservoir therefor the future well development can be

planned. It also helps the interpreter to know the occurrence of sandstone at sub-surface and

gives the geological information not only around the well but also in terms of 3D cubes. The

limitation of this study occurs due to the vertical resolution of seismic data which cannot

detect the thin layer, therefore the sandstone probability still hardly to define the thin layer at

the sub-surface. This study can still be continued into the advance analysis with using the

other supporting data.

Acknowledgments

The author would like to give the highest gratitude to Total E&P Indonesie for its permission

to publish this paper, and to Mr. Didiek Budhy Prabowo, Mr. Hilfan Khairy and Mr. M.

Adam Cepi from Total E&P Indonesie for their guidance during this study.

References Choliq, M. T., Yuh, S., Beele, M., Schulbaum, L., Vallon, G., 2014 . Seismic reservoir

characterization based on litho-seismic classification constrained by wells to detect gas-

bearing sands in Peciko Main Zone, Mahakam Delta, in: Proceedings of the International

Geosciences Conference and Exhibition, IPA, 38th Annual Convention. Jakarta

Hand, D. J., 1981, Discrimination and Classification: Wiley Series in Probabilities and Mathematical

Statisitics. John Wiley & Sons, Chicester

Lambert, B., B. C. Duval, Y. Grosjean, I. M. Umar, and P. Zaugg, 2003, The Peciko case history:

Impact of an evolving geologic model on the dramatic increase of gas reserves in the

Mahakam Delta, in M. T. Halbouty, ed., Giant oil and gas fields of the decade 1990– 1999,

AAPG Memoir 78, p. 297– 320.



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Figure 1. The study area of Peciko field is showed by the yellow square (a) and followed with the well

distribution at the study area (b)



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Figure 2. The simplified Litho-seismic classification workflow, where this process is intended to find

the operator that distinguish each lithologies in form of PDF map and will be applied on the inverted

seismic cube (modified from Choliq, M. T., 2014)

Figure 3. Crossplot of well data from elastic rock parameter P-Impedance (IP) and Poisson Ratio (PR)

at log scale after detrending with color code from lithology interpretation (before upscale). Each

lithologies is still overlapping and scattering around the crossplot.



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Figure 4. Crossplot of well data at seismic scale (a) and crossplot of inverted IP, PR data at seismic

scale by using the bandpass filter (6-30Hz) and upscaled lithology. Each lithologies has already

separated even though some points are still overlapping.

Figure 5. the PDF (Probability Density Function) operator for each lithologies from elastic parameter

IP, PR before extrapolating (a) and after extrapolating (b) which the probability is measured at unit %

meanwhile the colors that are showed at the most probable facies represents the lithologies (yellow for

sandstone, blue for limestone and green for shale or/and other facies)



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Figure 6. B-1 well as the reference well log data shows the probability (in unit of %) of each

lithologies on the ‘PDF of Lithology’ column with yellow color represents the sandstone, blue is

limestone and green is shale and/or other facies. The green symbol indicates the appropriate result,

orange symbol indicates the questionable result and red symbol indicates the doubtful result.



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Figure 7. N-14 well data shows the probability (in unit of %) of each lithologies on the ‘PDF of

Lithology’ column with yellow color represents the sandstone, blue is limestone and green is shale

and/or other facies. The green symbol indicates the appropriate result, orange symbol indicates the

questionable result and red symbol indicates the doubtful result.



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Figure 8. T-1 well data shows the probability (in unit of %) of each lithologies on the ‘PDF of






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Figure 9. M-1 well as the blind well log data shows the probability (in unit of %) of each lithologies

on the ‘PDF of Lithology’ column with yellow color represents the sandstone, blue is limestone and

green is shale and/or other facies. The green symbol indicates the appropriate result, orange symbol

indicates the questionable result and red symbol indicates the doubtful result.



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Figure 10. P-1 well data shows the probability (in unit of %) of each lithologies on the ‘PDF of






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Figure 11. Seismic section around reference well B-1 of inversion IP, PR cubes, lithology probability cubes (PDF of Sandstone and PDF of Limestone) and

the most probable facies cubes. Black line on the inset map represents the section and the blue line represents delineation of Mahakam delta. Pink circle

indicates the high probability of sandstone which confirmed on the most probable facies cubes.



Figure 12. Seismic section around N-14 well of inversion IP, PR cubes, lithology probability cubes (PDF of Sandstone and PDF of Limestone) and the most

probable facies cubes. Black line on the inset map represents the section and the blue line represents delineation of Mahakam delta. Pink circle indicates the

high probability of sandstone and orange circle indicates the high probability of limestone which confirmed on the most probable facies cubes.



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Figure 13. Seismic section around T-1 well of inversion IP, PR cubes, lithology probability cubes (PDF of Sandstone and PDF of Limestone) and the most


high probability of sandstone which confirmed on the most probable facies cubes.



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Figure 14. Seismic section around blind well M-1 of inversion IP, PR cubes, lithology probability cubes (PDF of Sandstone and PDF of Limestone) and the

most probable facies cubes. Black line on the inset map represents the section and the blue line represents delineation of Mahakam delta. Orange circle

indicates the high probability of limestone which confirmed on the most probable facies cubes. While, pink circle indicates the high probability of sandstone

but there was no sign of high probability of sandstone on the most probable facies cube.



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Figure 15. Seismic section around P-1 well of inversion IP, PR cubes, lithology probability cubes (PDF of Sandstone and PDF of Limestone) and the most


high probability of sandstone which confirmed on the most probable facies cubes. While, orange circle indicates the high probability of limestone but

unconfirmed on the most probable facies cube.



Figure 16. 1st layer of mid angle stack inversion cube and sandstone probability cube of elastic rock

parameter IP, PR at marker Beta until MF4. The black line is Mahakam PSC. IP, PR map layer shows

the probability of sandstone while Mid-Angle stack map layer shows the amplitude of seismic wave.



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Figure 17. 2nd layer of mid angle stack inversion cube and sandstone probability cube of elastic rock





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Figure 18. 3rd layer of mid angle stack inversion cube and sandstone probability cube of elastic rock



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