Abstract
Large-scale conglomerate fan-delta aprons were typical deposits on the slope of Mahu Depression during the Early Triassic. Without outcrops, it is difficult to study the lithofacies only by examining the limited cores from the main oil-bearing interval of the Baikouquan Formation. Borehole electrical imaging log provides abundant high-resolution geologic information that is obtainable only from real rocks previously. Referring to the lithology and sedimentary structure of cores, a case study of fan-deltas in the Lower Triassic Baikouquan Formation of the Mahu Depression presents a methodology for interpreting the complicated lithofacies utilizing borehole electrical images. Eleven types of lithologies and five types of sedimentary structures are summarized in borehole electrical images. The sediments are fining upward from gravel to silt and clay in the Baikouquan Formation. Fine-pebbles and granules are the main deposits in T1b1 and T1b2, but sandstones, siltstones and mudstones are more developed in T1b3. The main sedimentary textures are massive beddings, cross beddings and scour-and-fill structures. Parallel and horizontal beddings are more developed in T1b3 relatively. On integrated analysis of the lithology and sedimentary structure, eight lithofacies from electrical images, referred to as image lithofacies, is established for the fan-deltas. Granules to coarse-pebbles within massive beddings, granules to coarse-pebbles within cross and parallel beddings, siltstones within horizontal and massive beddings are the most developed lithofacies respectively in T1b1, T1b2 and T1b3. It indicates a gradual rise of the lake level of Mahu depression during the Early Triassic, with the fan-delta aprons retrograding towards to the margin of the basin. Therefore, the borehole electrical imaging log compensate for the limitation of cores of the Baikouquan Formation, providing an effective new approach to interpret the lithofacies of fan-delta.
1 Introduction
Lithofacies are defined mainly according to the grain size, sorting, rounding and texture of rocks. The term reflects some restrictive hydrodynamic condition in genetic units, which establishes definition and formal codification of standard lithological characters. Erected by Miall for analyzing alluvial fans and sinuosity rivers [1, 2], lithofacies codes have been widely used in interpreting the most modern and ancient deposits. The Mahu Depression is one of the largest hydrocarbon depressions in the Junggar Basin, northwestern China. Since 2010, successes have been achieved in hydrocarbon exploration and production of the Lower Triassic Baikouquan Formation. At the slope of the depression, the formation has been described as a succession of proximal coarse fan-delta deposits with complicated conglomerates in shallow water [3,4,5]. Because of no outcrops, the understanding of lithofacies was confined by the limited amount and quality of cores. Cores may be only taken in the key conglomerate reservoir in very few wells for the high cost and rig time concerns. It is difficult to interpret lithofacies just based on a few cores in the early stage of geological prospecting.
Borehole electrical imaging log, originated from 1980s, has served as advanced technology in logging geology. Very high-sample-density arrays are used in the oriented log tools to yield high-resolution information about micro-resistivity variations along the borehole wall. Visual intuitive borehole electrical images could then be gained by image processing functions [6,7,8]. The images provide a wealth of geologic data previously obtainable only from real rocks, therefore enabling the well logging to identify the lithology and sedimentary structure comparatively with cores [9, 10]. Thus, lithofacies, including the property of lithology and sedimentary structure, could be interpreted using borehole electrical images [11,12,13]. In this paper, after careful observation and description of cores, borehole electrical images are utilized to identify eleven types of lithologies and five types of sedimentary structures. Eight types of lithofacies from borehole electrical images are proposed for fan-deltas in the Baikouquan Formation of the Mahu Depression.
2 Geological setting
The Junggar Basin, the second largest basin in China, is located in Xinjiang Uygur Autonomous Region, northwest of the country (Figure 1a). As a result of collision and subduction between the Junggar-Turpan and Kazakhstan Plates in the Late Paleozoic, the foreland depression of Mahu formed at northwestern margin of the basin (Figure 1b) [14,15,16]. On the hanging wall of thrust fault, Zaire and Hala’alat mountains were denuded and supplied sufficient sediments for the Mahu Depression during the Early Triassic. One part of these coarse sediments accumulated at the margin of depression formed alluvial fans, while others moved further to the gentle slope by the interaction of gravity and water, resulting in a series of proximal fan-delta aprons in shallow water (Figure 1c). They are respectively called Zhongguai, Karamay, Huangyangquan, Xiazijie, Xiayan and Dabasong Fan-delta [3,4,5].
(a) Map of China, the Junggar Basin locates in northwestern China. (b) Location of the Mahu Depression in the Junggar Basin. (c) Plain figure of sedimentary facies of the Baikouquan Formation, the Mahu Depression. (d) Well logging and testing synthetic graph of the Baikouquan Formation, well M134.
The thickness of the Lower Triassic Baikouquan Formation (T1b), is 120-250 m. From bottom to top, it is divided into three members, marked as T1b1, T1b2 and T1b3. The lithologis of T1b1, with thickness of 30-50 m, are mainly gray, grayish-green and brown conglomerate imbedded thin brown mudstone. The lithologies of T1b2, with thickness of 60-100 m, are composed of thick interbeds of grayish-green conglomerate and brown mudstone. The major lithologies of T1b3, with thickness of 40-90 m, are gray sandstone and gray-brown mudstone (Figure 1d). Most cores are sampled at T1b1 and T1b2, which are major oil-bearing members. Only a few cores are sampled at T1b3 that is not rich in oil.
3 Database
Original data of borehole electrical imaging logging are tested in twenty-one wells: eleven wells in the Xiazijie Fan-delta and ten wells in the Huangyangquan Fan-delta (Figure 1c). The logging tools are FMI (Fullbore Formation MicroImager) of Schlumberger with 196 micro-electrodes on eight pads or XRMI (Extended-Range MicroImager) of Halliburton with 150 micro-electrodes on six pads. Both tools are with vertical resolution down to 5 mm in optimal conditions and provide far greater resolution than traditional wire-line tools. The dense samplings of micro-resistivity are processed usually by static and dynamic data filter to be converted into electrical images. A “static normalization” of the image takes the entire data set and again rescales the data to the highest and lowest values of the logging run, which subordinates rapid local changes in micro-resistivity to more general changes and preserves the gross lithology. A “dynamic normalization” takes the high and low values of micro-resistivity in a narrow “window” of data and rescales to corresponding values. The image artificially enhances the lithological changes and highlights bedding surfaces [17]. In order to interpret lithologies and sedimentary structures in this paper, 2D dynamic electrical images are processed in Techlog platform developed by Schlumberger Corporation. With gray-scale 0 to 255 in electrical images, resistive rocks are bright, whereas conductive material is dark. That is, the darker the color is, the lower the micro-resistivity of formation is. Stratifications appear in the images as straight lines or sine waves, and the amplitude of the sine waves reflects the dip relative to the borehole. Depth discrepancy between electrical imaging data and traditional wire-line logging data are corrected by gamma ray of both logging methods.
4 Methodology
4.1 Calibration of borehole electrical images
In order to correctly recognize the lithologies and sedimentary structures that are observed in the borehole electrical images, Donselaar and Schmidt suggested calibration of the images with the corresponding outcrop rocks or cores first [10]. The processing would reduce the uncertainty in the interpretation of the sedimentary features. In this study, the calibration is achieved to interpret variations in lithologies and sedimentary structures for the fan-deltas. There are fifteen electrical imaging logging wells with a few cores. Photographs of cores are taken or scanned in 360 degree. Based on the features of cores and electrical images, the calibration electrical images with core scanning photographs are carefully processed at depth scale of 1:5 (Figure 2). With a large depth scale of, sedimentary features of electrical images are evident enough to compare with that of cores. Since the electrical images are calibrated, lithology and sedimentary structure could be interpreted.
Calibration electrical images with 360 degree scanning photographs of cores at depth scale of 1:5, 2nd core run of well M19.
4.2 Lithofacies subdivision
Cores and outcrops provide the most important and accurate information of a geological formation. In traditional research methods, cores and outcrops are used to determine the lithfacies, assists in studying sedimentary microfacies and the whole depositional systems. However, cores and outcrops cannot give the researchers a full profile of geological body. Traditional research on lithofacies is merely valid in cored sections, but remains invalid in uncored intervals. Benefited from the borehole electrical imaging log, lithologies and sedimentary structures can be identified in one well rival the cores. Therefore, the well logging technology offers another effective method to interpret lithofacies by ultra-high-resolution images. For example, Shrivastva et al. identified four major lithofacies by integrating electrical images with cores to reconstruct deposition of Cretaceous Formation in eastern offshore India [11]. Based on the interpretation of lithology and sedimentary texture from electrical images and openhole logs, Xu et al. classified ten lithofacies to analyze the channel and non-channel elements in the Red Oak field, Arkoma basin [12]. Lack of cores, Folkestad et al. defined image facies to interpret delta and estuarine depositional systems in the North Sea [13]. As conventional lithofacies subdivision method of cores, lithofacies determination is just based on borehole electrical images, these lithofacies are defined as “image lithofacies” (IL) in this paper. The system of descriptive, simple of image lithofacies are established together with the internal eleven types of lithologies and five types of sedimentary structures for the fan-deltas in the Baikouquan Formation. The eight image lithofacies subdivision and corresponding descriptions are provided in the result below.
5 Results
5.1 Lithology identified by borehole electrical images
The grain size of sediments is one of the most important indexes of hydrodynamic condition. Grain size of rocks in the Baikouquan Formation has been classified by field researchers who discovered the conglomerate reservoirs. According to cores’ observation, the grain size is divided into four categories: gravel, sand, silt and clay. The gravels include boulder, cobble, coarse-pebble, fine-pebble and granule. Sands are subdivided into very-coarse, coarse, medium and fine (Table 1) [18, 19]. Due to the ultra-high-resolution and visualization, 2D electrical images offer elaborate characters for each type of lithology (Figure 3) [20]. Gravels show high resistivity with light spots. The spots suggest the approximate grain size of gravels: the coarser the gravels are, the bigger the spots are (Figure 3b, 3c, 3d, 3e). Exceptionally, gompholite display dark spots (Figure 3a). Sands show medium-high resistivity with yellow-light massiveness. The coarser the sand grains are, the lighter the images are (Figure 3f, 3g, 3h, 3i). Silt and clay show low-medium resistivity with dark-yellow images and low resistivity with dark images respectively (Figure 3j, 3k). With large depth scale of electrical images, lithology could be accurately identified for the entire Baikouquan Formation in one well.
Electrical images and core photographs of different grain size sediments. (a) Boulder gompholite, well FN401. (b) Cobble, well M152. (c) Coarse-pebble, well M19. (d) Fine-pebble, well FN10. (e) Granule, well AH1. (f) Very-coarse sand, well M152. (g) Coarse sand, well AH1. (h) Medium sand, well M152. (i) Fine sand, well M136. (j) Silt, well FN10. (k) Mud, well M152.
Grain size classification of the Baikouquan Formation in the Mahu Depression.
| Grain size | Gravel | Sand | Silt | Clay | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| boulder | cobble | coarse-pebble | fine-pebble | granule | very-coarse | coarse | medium | fine | |||
| mm | >128 | 32∼128 | 16∼32 | 8∼16 | 2∼8 | 1∼2 | 0.5∼1 | 0.25∼0.5 | 0.06∼0.25 | 0.004∼0.06 | <0.004 |
5.2 Sedimentary structure identified by borehole electrical images
Sedimentary textures can reflect the sedimentary environment. Five main types of sedimentary structures are observed from the cores of the Baikouquan Formation in the Mahu Depression: horizontal bedding, parallel bedding, cross bedding, massive bedding and scour-and-fill structure. Trough or tabular cross bedding cannot be distinguished from each other due to the small size of cores, both called cross bedding collectively. In 2D borehole electrical images, horizontal beddings, just developed in mudstone and siltstone, are dark straight lines with dips of 0 degree (Figure 4a). Parallel beddings are light straight lines with dips close to 0 degree (Figure 4c). Cross beddings are sine waves with different dips and inclinations (Figure 4b). Massive bedding has no obvious characteristic in images (Figure 4d). Scour-and-fill structures are erosive lithological interface with overlying spots and underlying dark massiveness (Figure 4e) [21,22,23]. Sedimentary structures can be recognized precisely as well at large depth scale.
Electrical images of different sedimentary structures. (a) Mudstones in horizontal bedding, 2779-2779.35 m and 2779.46-2779.55 m, well X721. (b) Granules in cross bedding, 3917-3917.68 m, well M18. (c) Granules in parallel bedding, 3533.9-3535.4 m, well M19. (d) Mudstones in massive bedding, 2727.8-2728.3 m; medium sandstones in massive bedding, 2728.3-2728.5 m; fine-pebbles in massive bedding, 2728.5-2729.3 m, well FN10. (e) Erosive interface, 3636.5 m, coarse-pebbles overlying and siltstones underlying, wellAH7.
5.3 Lithofacies identified by borehole electrical images
According to the characteristics of lithology and sedimentary structure in 2D borehole electrical images, eight double-property image lithofacies are summarized in Table 2 and illustrated by examples individually (Figure 5). Descriptions and interpretations of the image lithofacies are given below.
Lithofacies of borehole electrical images for the Baikouquan Formation in the Mahu Depression. (a) IL1, well AH2. (b) IL2, well M52. (c) IL3, well MZ1. (d) IL4, well FN401. (e) IL5, well M22. (f) IL6, well AH6. (g) IL7, well AH7. (h) IL8, well M152.
Summary of image lithofacies (IL) for the investigated Baikouquan Formation in the Mahu Depression.
| IL | Lithology | Sedimentary structure | Image characteristics | Possible microfacies |
|---|---|---|---|---|
| IL1 | disorganized gravels and sands | massive bedding | variable spots size | subaerial debris flow |
| IL2 | cobble to boulder | massive bedding | medium to big spots, no obvious characteristic | braided channel |
| IL3 | granule to coarse-pebble | cross bedding, parallel bedding | small to medium spots; spots in sine waves, light straight lines | braided channel, subaqueous distributary channel |
| IL4 | granule to coarse-pebble | massive bedding | small to medium spots, no obvious characteristic | subaerial debris flow, braided channel, subaqueous distributary channel |
| IL5 | fine to very-coarse sand | cross bedding, parallel bedding | yellow-light color; sine waves, light straight lines | braided channel, subaqueous distributary channel, sheet sand |
| IL6 | fine to very-coarse sand | massive bedding | yellow color; no obvious characteristic | braided channel, subaqueous distributary channel, sheet sand |
| IL7 | silt | massive bedding, horizontal bedding | yellow-dark massiveness, yellow-dark straight lines | inter-channel, interdistributary bay |
| IL8 | clay | massive bedding, horizontal bedding | dark massiveness, dark straight lines | inter-channel, lacustrine mudstone |
Image lithofacies-IL1
Description: In borehole electrical images, the dominated lithology cannot be classified. Sands and gravels are chaotic mixed. The size of spots in images is disorganized. The only sedimentary structure is massive bedding (Figure 5a). The thickness is 0.3-1 m.
Interpretation: Lithofacies of IL1 is commonly described within subaerial debris flow of fan-delta plain environment [24]. Because of the lack of sorting and stratification, the sediments are supposed to be deposited by the force of gravity rather than flows.
Image lithofacies-IL2
Description: The grain size of IL2 is cobble to boulder. Correspondingly, the spots size is large in electrical images. Because of the limited size of borehole, cross bedding cannot be recognized. The sedimentary texture is classified to massive bedding (Figure 5b). The thickness is 0.3-2 m.
Interpretation: Gravels of IL2 are coarse, which suggests that they are close to the provenance in the basin margin. The sorting is better than that of IL1. Therefore these gravels are possibly transported by currents. It is interpreted to be deposited in braided channel of the fan-delta plain [25].
Image lithofacies-IL3
Description: The grain size of IL3 is granule to coarse-pebble, with small to medium spots in images. In 2D electrical images, these spots include sine curves or straight lines, indicating apparent cross bedding or parallel bedding (Figure 5c). The thickness is 0.3-5 m.
Interpretation: Compared with that of IL2, the grain size of IL3 is smaller. The sorting and stratification are better than those of IL2. Cross bedding can be distinguished from massive bedding. This indicates that the gravels are transported farer toward the basin by currents. IL3 is commonly expounded to be deposited in braided channel or subaqueous distributary channel of the fan-delta front.
Image lithofacies-IL4
Description: The grain size of IL4 is the same as that of IL3. But obvious characteristic of sedimentary structure could not be observed in 2D electrical images. The sedimentary structure is massive bedding (Figure 5d). The thickness is 0.3-0.5 m.
Interpretation: The thickness of IL4 is generally less than other gravelly lithofacies. Potential microfacies are braided channel or subaqueous distributary channel. Lacking of stratification, sediments are also possibly transported by slumps and slides, which is called subaqueous debris flow of the fan-delta front [26,27].
Image lithofacies-IL5
Description: The lithology of IL5 is fine to very-coarse sandstone. In 2D electrical images, the color is uniform yellow-light within sine curves or light straight lines. The sedimentary structure is cross bedding or parallel bedding (Figure 5e). The thickness is 0.2-1 m.
Interpretation: The sedimentary characteristic of IL5 is similar to IL3.But the grains are finer. It reveals that with the decrease of hydrodynamic force, IL5 deposited at the top of gravelly braided channel or subaqueous distributary channel. Alternatively, IL5 is an important component of sandy subaqueous distributary channel of the fan-delta front.
Image lithofacies-IL6
Description: Same as IL5, the grain size of IL6 is fine to very-coarse sandstone. The color of 2D electrical images is yellow with no obvious characteristic. The sedimentary texture is massive bedding (Figure 5f). The thickness is 0.1-3 m.
Interpretation: Lacking of stratification, cross bedding and parallel bedding are not developed in IL6. The sorting is good in the electrical images. Possible microfacies are braided channels, subaqueous distributary channels or sheet sands of the fan-delta front [28].
Image lithofacies-IL7
Description: The lithology of IL7 is mainly siltstone. It is generally yellow-dark color within massiveness or straight lines in electrical images. Massive bedding or horizontal bedding could be observed (Figure 5g). The thickness is 0.1-1.5 m.
Interpretation: IL7 reveals relative quiet sedimentary environment. Probably, it deposits in ephemeral lakes on land or lake in the basin. The possible microfacies are the inter-channel of the fan-delta plain or the interdistributary bay of the fan-delta front.
Image lithofacies-IL8
Description: The lithology of IL8 is mudstone. The sedimentary structure is massive bedding or horizontal bedding. It is sometimes scoured by overlying gravels or sands (Figure 5h). The thickness is 0.1-0.5 m.
Interpretation: The lithofacies of IL8 is described within inter-channel or lacustrine mud of the pro-fan-delta. It is deposited in ephemeral lakes on land or lake in the basin, with no sediments supply, only clay is slowly deposited.
5.4 Lithofacies interpretation in single wells
Utilizing borehole electrical images, lithology and sedimentary structure of conglomerate are identified for the Baikouquan Formation in twenty-one wells. Based on the identified results, image lithofacies are interpreted for these wells. For example, the result of well AH013 is shown in Figure 6. Because of no cores in the Baikouquan Formation in this well, the electrical image is the only approach to study the lithology, sedimentary structure and lithofacies in the target formation.
Interpretation of image lithofacies in the Baikouquan Formation, well AH013. (a) T1b3. (b) T1b2. (c) T1b1.
In addition, according to the thickness statistics and analysis of image lithofacies (Figure 7), vertical variations of lithology and sedimentary structure in the whole Baikouquan Formation at one point are very obvious. The statistics of lithology indicate that sands are not developed in T1b1 or T1b2. The lithologies of T1b1 are mainly granules, fine-pebbles and mudstones, with a few boulders. The lithologies of T1b2 are mostly fine-pebbles, coarse-pebbles and granules. Granules, sands, siltstones and mudstones are developed in T1b3, with a few fine-pebbles (no boulder, cobble or coarse-pebble). From T1b1to T1b3, the sediment is fining upward from the fan-delta plain to the fan-delta front and the pro-fan-delta (Figure 7a). Massive beddings and cross beddings are the main textures in the Baikouquan Formation and its three members. Scour-and-fill structures are common between gravels and silts or clays. However, parallel and horizontal beddings are more developed in T1b3 than those of T1b1 and T1b2 (Figure 7b). According to the statistics of image lithofacies (Figure 7c), image lithofacies of T1b1 and T1b2 are mainly about IL3 and IL4, including a few of IL6, IL7 and IL8. Image lithofacies of T1b3 are about IL3, IL5, IL6, IL7 and IL8 (no IL1, IL2 or IL4). Granules to coarse-pebbles in massive beddings (IL4) is the most developed lithofacies in T1b1, while the most developed lithofacies in T1b2 is granules to coarse-pebbles in cross beddings and parallel beddings (IL3). Siltsones in horizontal beddings and massive beddings (IL7) is the most developed lithofacies in T1b3. Granules to coarse-pebbles are the main lithofacies in conglomerate reservoirs of T1b1 and T1b2, while sandstones, siltstones and mudstones are main lithofacies in nonreservoirs of T1b3. It indicates that lake level of the Mahu Depression in the Junggar Basin increased gradually during the Early Triassic. The fan-delta aprons retrograded towards the margin of the basin.
Thickness ratios of lithologies, sedimentary structures and image lithofacies of the Baikouquan Formation and its members, well AH013. (a) Thickness ratios of each lithologies based on borehole electrical images. (b) Thickness ratios of each sedimentary structures based on borehole electrical images. (c) Thickness ratios of each image lithofacies.
6 Discussion
Borehole electrical imaging log offers significant and valid evidence for late interpretation of microfacies and depositional environment of the fan-delta. Because of richness of hydrocarbon in T1b2 and T1b1, cores are mostly from these two members, and very few cores are taken in T1b3. Vertically all the cores could not cover the complete Baikouquan Formation. Because of the complicated and rapid change in the lithology of conglomerate reservoirs, it is very difficult to delineate the lithofacies by cores and conventional wire-line logging dates (especially in T1b3).
Without cores, previous workers tended to consider the top of T1b3belong to lacustrine sedimentation of the pro-fan-delta, with the high gamma ray and low resistivity in wire-line logging (Figure 8a). However, the alternated dark and bright signature is clear in the 2D borehole electrical images (Figure 8b). It reveals the occurrence of thin interbeds (about 0.5 m) of mudstones, siltstones and sandstones within horizontal or parallel beddings, rather than thick lacustrine mudstones. In borehole electrical images, the cross bedding is an important distinction between the subaqueous distributary channel and the braided channel (Figure 8c, 8d). Very thin mudstones and siltstones can be identified easily between channels. When mixed with gravels, sands and clays, the gamma ray value is higher and resistivity is lower in subaerial debris flow than gravelly channels. Lacking of sorting and stratification, it is difficult to identify this main lithology and obvious structure in borehole electrical images. Therefore, combined with conventional wire-line logging, the differences between subaerial debris flow and braided channel subaqueous or distributary channel are apparent to be interpreted (Figure 8a, 8e).
Interpretation result showing microfacies from borehole electrical images in uncored interval of the Baikouquan Formation, well M18. (a) Conventional well logs ofthe Baikouquan Formation. (b) Thin interbeds of mudstones, siltstones and sandstones in T1b3. (c) Subaqueous distributary channel and interdistributary bay in T1b2. (d) Braided channel and inter-channel in T1b1. (e) Subaerial debris flow with medium gamma ray and resistivity values in conventional well logging, T1b1.
7 Conclusions
Calibrated with cores, borehole electrical images are utilized to study the lithofacies of the fan-deltas in the Lower Triassic Baikouquan Formation in the Mahu Depression.
Based on lithology and sedimentary structure of cores, characteristics of eleven types of lithologies and five types of sedimentary structures are summarized. The lithology types include boulder, cobble, coarse-pebble, fine-pebble, granule, very-coarse sand, coarse sand, medium sand, fine sand, silt and clay. In 2D borehole electrical images, gravels are shown by light spots: the coarser the gravels are, the larger the light spots are. Sandstones show yellow-light massiveness: the coarser the sand grains are, the lighter the images are. Siltstones and mudstones show dark-yellow and dark color respectively. Sedimentary structures include horizontal bedding, parallel bedding, cross bedding, massive bedding and scour-and-fill structure. In the electrical images, horizontal beddings are dark straight lines, while parallel beddings are light straight lines. Cross beddings are sine waves and massive beddings have no obvious characteristic. Scour-and-fill structures are erosive lithological interface.
Combined with lithologies and sedimentary structures of electrical images, eight types of double-property image lithofacies are established to interpret the lithofacies of the fan-deltas. Granules to coarse-pebbles are the main lithology in T1b1 and T1b2, while sands, silts and clays are more developed in T1b3. Massive beddings and cross beddings are the main textures in the Baikouquan Formation, while parallel and horizontal beddings are more developed in T1b3. Granules to coarse-pebbles within massive beddings, granules to coarse-pebbles within cross and parallel beddings and siltstones within horizontal and massive beddings are the most developed lithofacies respectively in T1b1, T1b2 and T1b3. The lake level of the Mahu Depression in the Junggar Basin increased gradually during the Early Triassic, while the fan-delta aprons retrograded towards the basin margin.
Although the spatial resolution of features visible in the borehole electrical images is lower than that of cores or outcrops, borehole electrical imaging log offers interesting opportunities for sedimentological descriptions and interpretations both in cored and uncored intervals. It can assist in identification of major geologic structures penetrated by the well and can provide information about geologic characteristics with the absence of core data. The logging technology compensates the limitation of cores lithofacies of the Baikouquan Formation in the Mahu Depression, providing a new pragmatic approach to interpret the lithofacies. It offers significant and valid evidence and can be enhanced for future study on the microfacies and depositional environment for fan-deltas.
Acknowledgement
We are grateful to anonymous reviewers for their constructive reviews on the manuscript, and the editors for carefully revising the manuscript. This research is financially supported by National Naturel Science Foundation of China (No. 41772094), National Science and Technology Major Project (No. 2016ZX05027-002-007) and Innovation Fund of China National Petroleum Corporation (No. 2016D-5007-0104). The supports are gratefully acknowledged.
References
[1] Miall A.D., A review of the braided river depositional environment, Earth-Science Reviews, 1977, 13, 1-62.10.1016/0012-8252(77)90055-1Search in Google Scholar
[2] Miall A.D., Lithofacies types and vertical profile models in braided river deposits: a summary. In: Miall A.D. (Eds.), Fluvial Sedimentology, Canadian Society of Petroleum Geologists Memoirs, 1978, 5, 597-604.Search in Google Scholar
[3] Kuang L.C, Tang Y., Lei D.W, Wu T., Qu J.H., Exploration of fan-controlled large-area lithologic oil reservoirs of Triassic Baikouquan formation in slope zone of Mahu depression in Junggar basin, China Petroleum Exploration, 2014, 19(6), 14-23 (in Chines with English abstract).Search in Google Scholar
[4] Yu X.H., Qu J.H., Tan C.P, Zhang L., Li X.L, Gao Z.P., Conglomerate lithofacies and origin models of fan deltas of Baikouquan formation in Mahu sag, Junggar basin, Xinjiang Petroleum Geology, 2014, 35(6), 619-627 (in Chinese with English abstract).Search in Google Scholar
[5] Zou N.N., Shi J.A., Zhang D.Q., Ma C.Y., Zhang S.C., Lu X.C., Fan delta depositional model of Triassic Baikouquan formation in Mabei area, NW Junggar basin, Acta Sedimentologica Sinica, 2015, 33(3), 607-615 (in Chinese with English abstract).Search in Google Scholar
[6] Ekstrom M.P, Dahan C.A., Chen M.Y., Lloyd P.M, Rossi D.J., Formation imaging with microelectrical scanning arrays, SPWLA 27th Annual Logging Symposium, 1986, BB.Search in Google Scholar
[7] Plumb R.A., Luthl S.M., Analysis of borehole images and their application to geologic modeling of an eolian reservoir, SPE Formation Evaluation, 1989, 505-514.10.2118/15487-PASearch in Google Scholar
[8] Trouilier J.C., Delhomme J.P., Carlin S., Anxionnaz H., Thin bed reservoir analysis from borehole electrical images, SPE 19578, San Antonio, 1989, 61-72.10.2118/19578-MSSearch in Google Scholar
[9] Bourke L.T, Sedimentological borehole image analysis in clastic rocks asystematic approach to interpretation, Geological Society Special Publication, 1992, 65, 31-42.10.1144/GSL.SP.1992.065.01.04Search in Google Scholar
[10] Donselaar M.E., Schmidt J.M., Integration of outcrop and borehole image logs for high-resolution facies interpretation: example from a fluvial fan in the Ebro basin, Spain, Sedimentology, 2005, (52), 1021-1042.10.1111/j.1365-3091.2005.00737.xSearch in Google Scholar
[11] Shrivastva C., Ganguly S., Khan Z., Reconstructing sedimentary depositional environment with borehole imaging and core: A case study from eastern offshore India, IPTC, 2008, No.12253.10.2523/12253-MSSearch in Google Scholar
[12] Xu C.M., Cronin T.P., McGinness T.E., Steer B., Middle Atokan sediment gravity flows in the Red Oak field, Arkoma Basin, Oklahoma: A sedimentary analysis using electrical borehole images and wireline logs, AAPG Bulletin, 2009, 93(1), 1-29.10.1306/09030808054Search in Google Scholar
[13] Folkestad A., Veselovsky Z., Roberts P., Utilising borehole image logs to interpret delta to estuarine system: A case study of the subsurface Lower Jurassic Cook Formation in the Norwegian northern North Sea, Marine and Petroleum Geology, 2012, 29, 255-275.10.1016/j.marpetgeo.2011.07.008Search in Google Scholar
[14] Kuang J., Qi X.F., The structural characteristics and oil-gas explorative direction in Junggar foreland basin, Xinjiang Petroleum Geology, 2006, 27(1), 5-9 (in Chinese with English abstract).Search in Google Scholar
[15] He D.F., Yin C., Du S.K., Shi X., Ma H.S., Characteristics of structural segmentation of foreland thrust belts-A case study of the fault belts in the northwestern margin of Junggar basin, Earth Science Frontiers, 2004, 11(9), 91-101 (in Chinese with English abstract).Search in Google Scholar
[16] Meng Q.F., Xu Z.H., Xu H.M., Liu W.F., Wang G.H., Shang J.L., Qiu J.P., Characteristics and controlling over reservoir accumulation of tear fault in foreland thrust belt of Baikouquan area in the northwestern margin of Junggar basin, Journal of China University of Petroleum, 2008, 32(5), 18-21 (in Chinese with English abstract).Search in Google Scholar
[17] AAPG/Datapages, Atlas of borehole imagery, Tulsa, 2009.Search in Google Scholar
[18] Qu J.H., Zhang L., Wu J., You X.C., Characteristics of sandy conglomerate reservoirs and controlling factors on physical properties of Baikouquan formation in the western slope of Mahu sag, Junggar basin, Xinjiang Petroleum Geology, 2017, 38(1), 1-6 (in Chinese with English abstract).Search in Google Scholar
[19] Zhang C.M, Wang X.L., Zhu R., Qu J.H., Pan J., An Z.Y., Lithofacies classification of Baikouquan formation in Mahu sag, Junggar basin, Xinjiang Petroleum Geology, 2016, 37(5), 606-614 (in Chinese with English abstract).Search in Google Scholar
[20] Chen G.H., Wu W.S., Mao K.Y., Identifying formation lithology using formation microscanner images, Petroleum Exploration and Development, 2001, 28(2), 53-55 (in Chinese with English abstract).Search in Google Scholar
[21] Wu C.Y. (Eds.), Sedimentology of petroliferous basins in China, Petroleum Industry Press, Beijing, 1993, 70-85 (in Chinese).Search in Google Scholar
[22] Zhong G.F., Ma Z.T., Sedimentary structures identified fromhigh-resolution borehole micro-resistivity image logs, Journal of Tongji University, 2001, 29(5), 576-580 (in Chinese with English abstract).Search in Google Scholar
[23] Zhou L.X., Application of fullbore formation microimager (FMI) to study of glutenite sedimentary structures in Jiyang depression, Xinjiang Petroleum Geology, 2008, 29(5), 654-656 (in Chinese with English abstract).Search in Google Scholar
[24] Nemec W., Aspects of sediment movement on steep delta slopes. In: Colella A., Prior D.B., (Eds.), Coarse-grained deltas, International Association of Sedimentologists, 1990, 29-73.10.1002/9781444303858.ch3Search in Google Scholar
[25] Bridge J.S., Lunt I.A., Depositional models of braided rivers. In: Smith G.H.S., Best J.L., Bristow C.S., Petts G.E. (Eds.), Braided rivers: Process, deposits, ecology and management, International Association of Sedimentologists, 2006, 11-50.10.1002/9781444304374.ch2Search in Google Scholar
[26] Lowe D.R., Sediment gravity flows II: Depositional models with special reference to the deposits of high density turbidity currents, Journal of Sedimentary Petrology, 1982, 52(1), 279-297.10.1306/212F7F31-2B24-11D7-8648000102C1865DSearch in Google Scholar
[27] Mulder T., Alexander A., The physical character of subaqueous sedimentary density flows and their deposits, Sedimentology, 2001, 48(2), 269-299.10.1046/j.1365-3091.2001.00360.xSearch in Google Scholar
[28] Allen J.R.L., Studies in fluviatile sedimentation, bars, barcomplexes and sandstone sheets (lower-sinuosity braided streams) in the Brownstones (L. Devonian), Welsh Borders, Sedimentary Geology, 1983, 33(4), 237-293.10.1016/0037-0738(83)90076-3Search in Google Scholar
© 2017 R. Yuan et al
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
