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American Journal of Oil and Chemical Technologies: Volume 3. Issue 5. October 2015

Industrial And Mining Research Center – Cycle Science & Industry Comopany, Tehran, Iran

Email: [email protected]

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American Journal of Oil and Chemical Technologies

Journal Website: http://www.petrotex.us/

Study of Faults in Asmari Formation by FMI Image Log, Case Study:

Lali Oilfield

Erfan Hosseini1, Jalal Neshat Ghojogh

2, Bahram Habibnia

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1Abadan Institute of Technology, Petroleum University of Technology, Abadan, Iran

2Ahwaz Faculty of Petroleum Engineering, Petroleum University of Technology, Ahwaz, Iran

3Abadan Institute of Technology, Petroleum University of Technology, Abadan, Iran

Abstract

Identification and description of faults in an oilfield will help to prevent problems such as casing collapse, wellbore

instability, and hydrocarbon leakage. One way to study the performance of faults is using formation micro imager

logs. This type of log does this by fully imaging the wellbore wall. In this study major and minor faults were

recognized and assessed through analyzing raw data by means of GEOFRAME® software at interval of 1816-2050

m in well Lali-26. Abrupt change of bed dip direction from southwest to northeast at 1816 m showed that there is a

fault originated from over thrusting Asmari formation on Gachsaran formation. Furthermore there are several minor

faults at deeper than 1845 m, which were mainly identified by lithology contrast. All of studied faults had E-W

trend. The minor faults may be caused by compression of lower block in main fault.

Keywords: Fault, Lali, Asmari, Formation Micro Imager, Gachsaran

1. Introduction

Once reservoir section drilled, only a minor proportion will be cored, and one may find that only exceptionally are

faults and fractures present in the core material. The main reason is that brittle tectonic deformation is scarce away

from faults, and drillers are hesitant to cut cores across faults because of the risk of jamming and potential pressure

problems. Moreover, some cored fault rocks may be so unconsolidated that fall apart to form what is known as

rubble zones. However, successfully cored faults and damage zones represent valuable information [6]. An

alternative to solve this problem is to create a continuous micro resistivity image of the borehole based on the

resistivity data from more sophisticated tools, such as Formation Micro Imager (Figure 1). This tool measures micro

resistivity by means of a few hundred electrodes. The outcome of this method is a continuous image of the wellbore

wall that is reminiscent of an actual picture of the rock [3]. The major purpose of this paper is to study the

performance of minor and micro faults acting in Lali oilfield by FMI and extend the results of interpretation to

macro scale.

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Authors /American Journal of Oil and Chemical Technologies 5 (2015)

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Figure 1. Correlating the resistivity values to equivalent spectrum of colors [5].

2. Geological Description of Lali Oilfield

Lali oilfield is located in the region of northern Dezful at 112 km northeast of Ahwaz (Figure 2), this anticline is an

asymmetrical structure with NE-SW trend and southern flank dip is higer than northen flank, and causes to change

the axis to follow west trend in northern part and southern trend in the west. Thickness of Asmari reservoir in this

field is about 400 m and is divided to 7 zones based on petrophysical data. Most important character of Asmari is

presence of extended natural fracture systems which causes high productivity of wells not withstanding low matrix

porosity (8% on average) [1,5].

Figure 2. Location of well Lali-26 and main fault in Lali oilfield [2, 5].


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3. Faults and Image Logs

Fault is generally defined as any surface or narrow zone with visible shear displacement along the zone [3]. One of

important applications of image logs is identification and description of faults [2]. Once the image gathered from

wellbore is “unwrapped” and displayed from 0° to 360°, fault crossing the borehole appears as sinusoid [7].

Assuming that the images are properly oriented to the geographic north, the peaks and troughs of the sinusoids are

related to the dip and azimuth of the fault, respectively. This therefore provides essential information about the

formation encountered that other petrophysical logs are unable to provide. Figure 2 indicates typical response of a

fault with details on FMI log. Only faults with displacement less than wellbore diameter is observable on image logs

[8]. Figures 3 and 4 show normal and reverse faults with displacements less than wellbore diameter.

Figure 2. Typical response of fault and its parameters on FMI logs [2].

Figure 3. Identification of normal fault by FMI [2].


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In case where fault displacement is higher than wellbore diameter indirect observations such as structural dip

change, truncated bedding, displacement of sedimentary layers, high angle planar contact between different

lithologies, high concentration of fractures in sheared zones, secondary mineralization, brecciation, abrupt change in

well trajectory, and development of borehole breakout (Figure 5) are signs of possible fault.

Figure 4. Representation of trust fault on FMI log [2].

Figure 5. Development of borehole breakout and its extension to higher depths [2].

4. Methodology

Gathered raw data from well Lali-26 were processed and interpreted by modules of GEOFRAME® as observable in

Figure 6. Image log processing includes procedures which remove errors, enhance quality of logs and

autocomupting parameters such as dip and strike of geological events. In next stage the main and minor faults were

identified and matched with cross section of oilfield near well Lali-26.


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Figure 6. Data processing by GEOFRAME

® modules [2].

5. Results & Discussion

5.1. Identification of Faults in Asmari Formation of Lali Oilfield

5.1.1. Main Fault

By interpretation of FMI log corresponding to well Lali-26 in Asmari top different faults were identified.

According to Figure 3, at shallower than 1816m beds dipped toward southwest, by going deeper dip angle

increases and dip direction turns to northeast at 1816 m which could be indication of fault. This hypothesis were

confirmed by cross section which is shown in Figure 5.

Figure 3. Main fault acting in well Lali-26 in Asmari reservoir

on FMI log with possible signs.


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Figure 4. 3-D representation of main fault acting in well

Lali-26.

It should be stated that in addition to 9 criteria mentioned earlier, drilling condition, knowledge about geological

situation of area, seismic profiles, and even downhole pressure data can be also useful in detection of faults in an

area. Faults will be detected and analyzed by considering following observations:

Down falling the cap rock and Asmari horizon compared to drilling forecasting program, which could be

due to performance of faults present in the well.

Analyzing the seismic profiles shows that this well is close to main fault which influence the FMI log

(Figures 5, 6).


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Figure 5. Structural cross section of well under study indicating the main fault and other minor faults in Asmari

reservoir of Lali oilfield.

Figure 6. Regional view of main fault acting in Lali oilfield [4].


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Output of processing dip data by GEOFRAME® is shown in Figure 7. Depth at which dip direction changes

suddenly is location of main fault.

Figure 7. Structural cross section from interpretation of bedding dip angle and direction measured by FMI in one of

well Lali-26 [2].

5.1.2. Minor Faults

Minor faults extended lower than main fault is demonstrated in Figures 8-12. According to these figures, lithology

contrast is a key factor to identify fault. It should be mentioned that appearance of lithology of anhydrite and shale is

due to over thrusting Asmari formation on Gachsaran formation which could be attributed to difference between

strength of Asmari and Gachsaran formation.


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Figure 8. Demonstration evidences of minor fault at 1845 m in well under study on FMI log.


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Figure 9. Representation of fault existing at depth of 1851 m and 1856 m in well under study along with evidences

on FMI.


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Figure 10. Demonstration of fault existing at depth of 1960 m in well under study along with evidences on FMI.


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Figure 11. Demonstration of fault existing at depth of 1856 m in well under study along with evidences on FMI and

structural profile.


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Figure 12. Demonstration of fault existing at depth of 2050 m in well under study along with evidences on FMI.

6. Conclusions & Recommendations

Results which were obtained from analysis of bedding and fault strike and dip by FMI log had good correlation with

2-D cross section. Bedding dip change and lithology contrast were the key factors in identification of main and

minor faults, respectively. Main fault was originated from over thrusting Asmari formation on Gachsaran formation.

Acknowledgement The Authors would like to thank department of geology of NISOC Company because of providing image logs and

data and also scientific consultant.

7. References

[1] Saedi, G., Soleimani, B., Charchi, A., Taghavipur, S., Identification and Analysis of Fractures Exiting in one

Well in SE Iran using by FMI Image Log, the 1st International Applied Geological Congress, 26-28 April,

Mashad, Iran.

[2] Movahed, Z, Dashti, R. & Chakravorty, S., 2007, "Geological and petrophysical analysis of FuIIBore

Formation Micro Imager(FMI), Feild Ahvaz, Well #383", Well Services of Iran (Schlumberger Methods),

Report NISOC, No. p-5627, 64 pp.

[3] Fossen, H., Structural Geology, Cambridge University press, New York, first edition, 2010.


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[4] Mohammadian, R., Taghavipoor, Sh., Ghanavati, K. & Karami, M., 2011, "Statistical analysis of fractures

and investigation relative effects of reservoir parameters by fracture modeling in one of the south west oil field

of Iran", 14th. International oil, gas and petrochemical congress, No. 8971, 2 pp.

[5] Noraei Nezhad, Kh., Amiri Bakhtiar, H., Mohammadian, R., Azizi, A., Consideration of Geometric and

Kinetic Parameters Fractures of Asmari Reservoir in Marum Field, Scientific Quarterly Journal, Geosciences,

Vol. 24, No. 93, Autumn 2014.

[6] Abraham, M. L., Investigation of Thin Bed Strata Using Borehole Image Log And High Resolution Seismic

Data, Ph.D. dissertation, University of Oklahoma, 2005.

[7] Rider, H., 1996. The Geological Interpretation of Well Logs. Gulf Publishing.

[8] Ye, S., Rabiller, P., 1998. Automated fracture detection on high resolution resistivity borehole imagery. In

SPE annual technical conference and exhibition 777–784 pp.

study of faults in asmari formation by ... - petrotex library

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