PROCEEDINGS, INDONESIAN PETROLEUM ASSOCIATION Thirty-Ninth Annual Convention & Exhibition, May 2015

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1 IPA15-G-113 PROCEEDINGS, INDONESIAN PETROLEUM ASSOCIATION Thirty-Ninth Annual Convention & Exhibition, May 2015 FRACTURE SHALE GAS STUDY OF TANJUNG FORMATION BARITO BASIN, SOUTH KALIMANTAN Dian Larasati* Fikri Muhammad Fiqih** Raden Idris*** Djedi S. Widarto* Benyamin Sapiie**** ABSTRACT Fracture has become a critical factor in enhancing the permeability potential of shale in producing gas. Shale gas may be stored as a free gas in fractures and intergranular porosity, so the developed well connectivity between pores and fractures is needed. A deeper understanding of the fracture shale gas of the Tanjung Formation, Barito Basin, South Kalimantan was carried out in this study. This area was covered because it has a high potential for shale gas, about TCF from the previous study. All core samples from the field show that shale has a low porosity, consisting of intergranular, secondary porosity, micro fracture, and micro porosity. Pores seen from scanning electron microscopy (SEM) are not interconnected because of the abundance of detrital clay matrix, cementation, and replacement. Petrographical analyses of thin sections in the shale supported the SEM analyses. X-Ray Diffraction analysis showed that the Tanjung Formation has high quartz content and a low concentration of smectite as a swellingclay mineral. From this analysis, the brittleness index (BI) could be obtained and could be used as a cut-off to calculate the volumetric of shale gas, along with the geochemical analysis. Lithofacies, porosity and permeability, geochemical characteristics, and geomechanical properties analyses are fundamental basic data in creating the shale volumetric, as a key to creating fracture modeling. We used the Discreet Fracture Network (DFN) Model to integrate the field and subsurface data. This DFN Model is created by using a fracture intensity guide that used the fracture intensity, BI, and FMI data. * Pertamina UTC ** Pertamina Hulu Energi *** Pertamina EP **** LAPI ITB From this model, we know that the highest intensity of fracture is located at the zone near the fault and the high folded area with the highest BI. Keywords: Shale gas, fracture, permeability INTRODUCTION Geology Overview of Barito Basin The Barito Basin was formed at Early Cenozoic (Hall, 2002), located along the Sundaland in the southeast (Figure 1). In the west, this basin is bounded by the Schwaner Mountains, which consist of contact and regional metamorphic rocks, plutonitic and granitic rocks, and volcanic rocks. In the east, this basin is bounded by the Meratus Complex, mélange, and ophiolit that separated the Barito and Asam-Asam basins. In the south, this basin is elongated and narrowed into the Java Sea. In the north, this basin is bounded by the Adang Flexure and identified by the changing lithofacies at Lower Oligocene (Witts et al., 2012). Two tectonic elements controlled the formation of Barito Basin: Meratus Complex and Adang Fault (Mason et al., 1993). Tectonically, the Barito Basin is divided into three periods: Eocene rifting, uplifting of Meratus Complex at Middle Miocene, and upthrust faults at Plio-Pleitocene (Pranajaya et al., 2007). Kusuma and Darin (1989) classified the tectonostratigraphy of the Barito Basin into four sequences: pre-rift, syn-rift, post-rift, and syn inversion (Figure 2). The syn-rift sequence started after the collision between the Indian Plate, Eurasian, and the west of the Pacific Plate about 50 million years ago (Middle Miocene), consisting of sandstone, siltstone, claystone, and conglomeratic stone, with coal as a minor constituent. Post-rift

2 sequences, Lower to Upper Tanjung Formation and Berai Formation, were deposited during the burial phase at Middle Eocene to Early Miocene. The burial phase still occurred in Oligocene and Middle Miocene. Carbonaceous sediment from the Berai Member filled this basin. The syn-inversion sequence consists of the Warukin and Dahor formations. Sediment from the Warukin Formation was deposited as the result of continental crust uplifting in the west and Meratus uplifting in the east, consisting of shallow marine and marginal marine clastic sediments, such as sandstone, claystone, siltstone, and coal. The last intensive tectonic activity occurred at Plio-Pleistocene and reactivated the Meratus Complex. The terminology of syn-inversion is actually not appropriate because there are no indications of rift-graben and relative movement of inverted faults. In this case, sedimentation occurred when Meratus was uplifted, becoming the Mountain Complex. Syn-orogenic or syn-uplift is more appropriate for this case (Pranajaya et al., 2007). Data Source Core samples from the field, in this case from the Tanjung Formation, were used to identify lithofacies and rock characteristics. Thirty-five locations of outcrops were divided into five observation areas: Cempaka, Pengaron, Binuang Baramarta, and Bentot, as shown in Figure 3. Ten samples with variable depths with the maximum depth at 2 m, were taken to represent those five observation areas, along with hand samples. Subsurface analyses were based on the well and seismic data. Seven wells were used for the wireline log and geochemical analyses, with 307 sections of two-dimensional seismic lines and 1 cube of threedimensional (3D) seismic lines in the Tanjung Block owned by Pertamina. METHODS Laboratory analyses for the field samples were undertaken to know the lithofacies, porosity and permeability, geochemistry, and geomechanical characteristics. In this study, wireline log data from the seven wells were also used for petrophysical analyses. These wells were also used for correlation and data calibration, especially for the geochemistry characteristics. Lithofacies, porosity and permeability, geochemical characteristics, and geomechanical properties analyses are fundamental as basic data in creating shale volumetric, as a key to creating fracture modeling. We used the Discreet Fracture Network (DFN) Model to integrate the field and subsurface data. This DFN Model is created by using a fracture intensity guide, which used the fracture intensity, brittleness index (BI), and FMI data. RESULTS Field Geological Analyses These analyses include the lithofacies identification, porosity and permeability, geochemistry, and geomechanics from field samples. a. Lithofacies Identification To identify the lithofacies, we used sedimentology and stratigraphy analyses, supported by petrography of thin section analysis. From the sedimentology and stratigraphy analysis, the lower part of the Tanjung Formation consists of conglomerate and pebbly sandstone with quartz, chert, red sandstone, mudstone, and litic fragments. The middle part consists of sandstone, mudstone, and coal seam, with a wide lateral distribution of approximately 3 m in thickness. The upper part is affected by marine environment where marine shale and limestone are deposited (Figure 4). Petrography of thin section samples used seven samples from several observation points (Figure 5) selected based on shale characteristics found in the field and delivered for the petrography analysis. The general result shows that the thin section of the Tanjung Formation consists of detrital fragment. b. Porosity and Permeability Analyses Eight core samples were analyzed for porosity and permeability testing in the laboratory. Porosity and permeability tests were done by adding pressure to the sample to make a calculation. A combination of porosity and permeability tests gave high values, not realistic for shale. Fractures formed during the coring process could be the cause of these anomalies. c. Scanning Electron Microscope (SEM) Analysis SEM analysis was used for observing the pores and the connectivity between those pores, fragment morphology, and the element

3 compositions. Six samples from the Barito Basin were taken into these analyses: two from the Lower Tanjung Formation, two from the Middle Tanjung Formation, and two from the Upper Tanjung Formation. The Upper Tanjung Formation differed from the Middle and Lower Tanjung formations by the occurrence of the carbonate material, because this formation was deposited in a marine environment. SEM analysis shows that the Upper Tanjung Formation consists of fine sandstone with quartz, k-feldspar, plagioclase, and clay mineral. This sample is characterized by lamination in thin sections, while the Middle and Upper Tanjung formations have a silty texture and mostly consist of clay minerals: illite, kaolinite, and chlorite. All samples show a low porosity of intergranular, secondary porosity, micro fractures, and micro porosity (Figure 6). SEM analysis is supported by petrography analysis on thin section in pores, pores conductivity, micro fractures, and mineral observations. d. Geochemical Analysis Rock-Eval is the most widely used technique to characterize source rock. The important parameters in this study are organic material content that could be extracted from the source rock (peak of S1 in gas chromatography) and residual kerogen (peak of S2). Eleven samples were delivered to the geochemical laboratory, but unfortunately, the results were not suitable and did not reflect the subsurface environment. e. X-Ray Diffraction (XRD) and Geomechanics Analysis XRD analyses were performed to obtain the mineral composition of shale from the Tanjung Formation. This analysis show that the shales have a high quartz content (up to 55%) and high clay mineral (up to 70%), shown in Table 1. Low concentration of smectite as swelling clay is good sign of the geomechanics side in drilling. From the other side, high kaolinite and illite are still debatable in geomechanics. High quartz content could equalize this parameter. The BI is obtained from the combination of XRD and geomechanics (Table 2) by using the formula from Wang and Gale (2009): BI = (Q + Dol)/(Q + Dol + Lm + Cl + TOC) where BI = brittleness index Q = quartz (%) Cl = clay (%) Dol = dolomite (%) Lm = limestone/calcite (%) TOC = total organic carbon (%) The average TOC value of the sample is 0.48, corresponding to the subsurface data and could be used as a cut off in volumetric calculation. The result of the BI calculation is represented in Table 2. f. Structural Geology Analysis The structural geology in the research area shows a NE SW trend, following the Meratus Complex trend. Other geological features are folds, reverse faults, and strike slip faults. Well Analyses Well analyses in this study were done to obtain the shale gas potential of the Tanjung Formation, such as the content of free gas, TOC, and BI that would be input data in distributing the petrophysical properties to the geological model. a. Well Correlation Lithostratigraphic framework (formation) is a basic tool in undertaking the well correlation to visualize the general distribution of the Tanjung Formation. The horizons from the bottom to the upper part are Basement, Lower Tanjung, Middle Tanjung, Upper Tanjung, Berai, and Warukin Formation. An index map of the E W and N S correlations is shown in Figure 7. Well sections were created to represent the formation distribution. From E W (Figure 8) through Bagok-1, SJG-1, and Maridu-1, this section represents structure (flattened in the top of the well) and stratigraphy (flattened on Upper, middle, and lower Tanjung Formation). These sections show that the Tanjung Formation is thinning to the west, with the main depth of the basin located around the Maridu-1 Well. b. Petrophysical Analyses These analyses were volume shale (Vshale), porosity (Phi), water saturation (Sw), TOC, and BI calculation.

4 The Vshale calculation used gamma-ray logs based on minimum and maximum readings for each zone. The minimum reading of the gamma ray represents sandstone zone, while the maximum reading represents shale zone. The porosity calculation was done using neutron and density logs cross plots. This method combines two logs: neutron and density. For this calculation, shale correction should be done to determine effective porosity because of the occurrence of bound water in shale. In this study, a water saturation calculation was done using the Shaly-Sand Method (Modified Simandoux). This method was selected because the Tanjung Formation is composed of shale and sandstone in its rock body. The TOC calculation used Passey et al. s (1990) method. This method is generally known as log R, by combining resistivity and sonic curves. This method can be used to identify and calculate the TOC in organic-rich rocks by using well log data. The TOC in a rock interval is represented by the separation of resistivity and the sonic curve. The Level of Organic Metamorphism (LOM) is obtained from plotting between TOC and S2 value. Mineralogy analysis, such as XRD, can be used to predict the BI of rocks. The BI value can be calculated by using the Jarvier equation: volume of non clay minerals Brittleness index = volume of total minerals Based on XRD analysis, quartz and siderite are the most common minerals besides the clay minerals, while illite, chlorite, and chlorite are the most common clay minerals. It affected the Jarvier equation as follows: %Quartz + %Siderite BI = %Quartz + %Siderite + %Illite + %Kaolinite + %Chlorite Seismic Interpretation The seismic data of the research area show fair to bad quality. The seismic reflection shows a bad to fair continuation, except on the basement that gives a chaotic pattern. Interpretations were done toward six horizons, following marker data available in the well. The order of seismic stratigraphy from the oldest to the youngest are Top Basement, Top Lower Tanjung, Top Middle Tanjung, Top Upper Tanjung, Top Berai, and Top Warukin Formation. a. Subsurface Mapping Time and depth structure maps, contouring, and gridding resulted from the time picking and check shot data. A depth structure map was created based on check shot data. The result shows that the research area is controlled by faults with NE SW trend in the north and east. b. Geological Section Generally, the research area is a fold-thrust belt zone, with NNE SSW trend. Based on the fold trend and thrust faults created, the main stress in this area is predicted as NW SE. Geological Model This geological section is created as integration between seismic and surface geological data. Based on the section with the NW SE trend (Figure 9), the research area is a lower zone uplifted because of a thick skin thrust fault as an inversion of normal faults in the east (Meratus Complex Zone) and in the north (Kambitin Anticlinorium), where the Berai and Tanjung formations started to be exposed. a. Geostatistics Model The aim of this geostatistics approach was to estimate the alternative value of reservoir properties in locations without having samples. The geostatistics model includes creating the structural and property models. Structural modeling is a process creating a 3D grid model to obtain the boundary limits of petrophysical modeling, while the property (petrophysical) modeling is a process distributing the petrophysical value of all cells from a 3D grid model using certain distribution methods. Generally, the process of this petrophysical modeling is a continuation of creating the 3D grid model that would be then integrated with the results of well log data. In this study, we created the model of Vshale (Figure 10), phie (Figure 11), Sw (Figure 12), TOC (Figure 13), and BI (Figure 14). b. Discreet Fracture Network (DFN) Model Based on direct observations in the field, fractures developed in the shale could be

5 classified into shear fractures. This contradicted the early hypothesis that the fractures are similar to cleats in coal. But in the area round the Kambitin Anticlinorium, we found fractures with similar characteristics to cleats. This predicted that the fractures are associated with the folds. From these field facts, we created fracture modeling using a DFN model, which integrates the field and subsurface data. This DFN model is created using a fracture intensity guide resulting from: Fracture intensity vs. BI from the field data Fracture intensity vs. maximum curvature from seismic data Fracture intensity vs. Distance to Fault from FMI data (partial conductive fracture) Fracture intensity from the field could be in the form of 1D-scanline observations. In this case, the basic data is an opening mode fracture that has a parallel trend with the main compression stress obtained from the geological structures on the subsurface. Based on this model, the highest intensity is located at the zone near the faults with a high BI, and it is a strong folded zone with high BI (Figure 15). CONCLUSIONS The Tanjung Formation has an average TOC value of wt%, with LOM 11 based on petrophysical analysis. This formation has an average TOC value about wt% based on field and well data. Shale from the Tanjung Formation consists of quartz, clay mineral, K-Feldspar, plagioclase, and siderite. The clay mineral consists of illite, kaolinite, and chlorite. Integration between seismic and surface data indicates that the research area is a lower zone that has been uplifted because of the thick skin thrust fault. This fault is the inversion of normal faults in the east (Meratus Complex Zone) and in the north (Kambitin Anticlinorium), where the Berai and Tanjung formations started to be exposed to the surface. ACKNOWLEDGMENTS The authors convey sincere appreciation to the management of PT Pertamina (Persero), PT Pertamina Hulu Energi, PT Pertamina EP, and the Directorate General of Oil and Gas for their permission and encouragement to publish and present this paper. REFERENCES Hall, R., 2002, Cenozoic Geological and Plate Tectonic Evolution of the SE Asia and the SW Pacific: Computer-Based Reconstruction, Model and Animations. Journal of Asian Earth Sciences, 20, Kusuma, I., Darin, T, 1989, The Hydrocarbon Potential of the Lower Tanjung Formation, Barito Basin, SE Kalimantan. Indonesian Petroleum Association, 18th Annual Convention, Jakarta, Mason, A.D.M., Haebig, J.C., McAdoo, R.L., 1993, A Fresh Look at The North Barito Basin, Kalimantan. Indonesian Petroleum Association, 22nd Annual Convention, Jakarta, 1993, i.1, Passey, Q.R., Creaney, S., Kulla, J.B., Moretti, F J., Stroud, J.D., 1990, A Practical Model for Organic Richness from Porosity and Resistivity Logs. The American Association of Petroleum Geologists Bulletin, 74, 12, Pranajaya, G., Idris, R., Arifin, M., Imron, M., 2007, Petroleum System and Sub Basin Distribution in Tanjung Block, Barito Basin, South Kalimantan. Proceedings Joint Convention Bali, The 32nd IAGI, The 36th IAGI, and The 29th IATMI Annual Conference and Exhibition. Wang, F.P., Gale J.F.W., 2009, Screening Criteria for Shale-Gas Systems: GCAGS Transactions, 59, Witts, D., Hall, R., Nichols, G., Morley, R., 2012, A New Depositional and Provenance Model for The Tanjung Formation, Barito Basin, SE Kalimantan, Indonesia, Journal of Asian Earth Sciences, 56,

6 TABLE 1 XRD ANALYSIS OF THE FIELD SAMPLE. ELEVEN SAMPLES FROM FIVE OBSERVATION AREAS FOR THIS STUDY CLAY MINERALS (%) CARBONATE MINERALS (%) OTHER MINERALS (%) TOTAL (%) NO SAMPLE SMECTITE ILLITE KAOLINITE CHLORITE CALCITE DOLOMITE SIDERITE QUARTZ K-FELDSFAR PLAGIOCLASE PYRITE CLAY CARBONATE OTHER 1 BBPK-1 SL2 NF BBPK SL2 NF BBPK-1 SL-1 NF BBPK-1 SL-1 NF ABC-1 NF ABC-1 NF KCM-1 NF KCM-1 NF KCM-2 NF KCM-2 FR BRM-CORE TABLE 2 THE RESULTS OF BI CALCULATION. THE AVERAGE BI VALUE IS 0.48, WHICH CORRESPONDS TO THE SUBSURFACE DATA AND COULD BE USED AS CUT-OFF IN VOLUMETRIC CALCULATION. SAMPEL BBPK-1 BBPK SL2 SL2 NF 200 NF 1010 BBPK-1 SL- BBPK-1 SL- ABC-1 NF 1 NF NF ABC-1 NF 100 KCM-1 NF 2730 KCM-1 NF 2790 KCM-2 NF KCM-2 FR BRM-CORE 2 INDEKS KEKERASAN

7 Figure 1 - Tectonic setting of Southeast Asia. Barito Basin is located along the Sundaland that is relatively stable (Hall, 2002).

8 Figure 2 - Regional stratigraphic column of Barito Basin (Kusuma and Darin, 1989). It is reflected in the tectonostratigraphic event of the basin into four sequences: pre-rift, syn-rift, post-rift, and syn-inversion.

9 Figure 3 - Map of the research area with the observation location. The purple box represents the research area while the black box represents the observation area.

10 Figure 4 - This picture show the carbonaceous shale bed with intercalated siltstone as a part of Upper Tanjung Formation, located in the ABC-1 observation area.

11 Feldspar grain Feldspar grain Recrystallized and orientation of clay materials Muscovite grains Recrystallized and orientation of clay materials Muscovite grains Foraminifera fragment Foraminifera fragment Quartz grains 0.5 mm Quartz grains 0.5 mm PPL Figure 5 - This is an example of thin section samples observed in petrography laboratory. This sample show that the dominant component is the clay mineral with some materials having a measurement of silt. XPL

12 Figure 6 - SEM analysis from BPPK-1 sample that represents micro fractures and unstable mineral dissolution.

13 Figure 7 - Index map of the well correlation from a) west-east and b) south-north. The blue shape represents the research area.

14 Figure 8 - E W correlation (flattened in the top of measured depth). This correlation represents stucture and stratigraphy of the research area.

15 Figure 9 - Seismic interpretation of NW SE trend, represented by the yellow line in the index map.

16 Figure 10 - Model of Vshale distribution; the yellow zone represents high probability occurrence of sandstone (Vsh = 0 0.5), while the green zone represents high probability occurrence of shale (Vsh 0.5 1).

17 Figure 11 - Model of phie distribution; the pink zone represents relatively low porosity rocks (phie = 0), while the red zone represents relatively high porosity rocks (phie = 0.225).

18 Figure 12 - Model of Sw distribution; the red zone represents low water saturation (Sw = 0), while the blue zone represents high water saturation (Sw = 1).

19 Figure 13 - Model of TOC distribution: the purple zone represents low TOC (TOC = 0), while the red zone represents high TOC (TOC = 1.8).

20 Figure 14 - Model of BI distribution: the purple zone relatively ductile rocks (BI = 0.375), while the red zone represents relatively brittle rocks (BI = 0.8).

21 Figure 15 - a) Fracture Intensity Model: the purple zone represents lower probability of fractures occurrence than the red zone b) The visualization of fracture modelling as DFN Model with a NW SE trend.