# Seismic Identification and Characterization of Deep Strike-Slip Faults in the Tarim Craton Basin
## 1 Introduction  
Strike-slip faults in cratonic basins, such as ruptures, are the products of pre-existing structures responding to stress concentrations within the craton. These faults are notably situated a significant distance away from active plate boundaries [1, 2, 3]. A distinguishing feature between intra-cratonic strike-slip faults and other large-scale strike-slip faults, such as those found at plate boundaries or embedded collision zones, lies in their slip distances, with the former typically ranging from hundreds to thousands of metres and the latter commonly extending to hundreds of kilometres [4]. Characterized by weak activity and high steepness, these strike-slip faults are difficult to identify with two-dimensional seismic data and are often overlooked [5, 6]. Recent oil and gas discoveries related to strike-slip faults in deep and ultra-deep strata within cratonic basins have underscored their substantial role in controlling reservoir development and hydrocarbon accumulation,giving rise to the \"near-source and fault-controlled\" model [7]. Nevertheless, accurately characterizing these complex strike-slip faults using conventional seismic interpretation methods is difficult because of the limitations of low signal-to-noise ratios and resolutions in seismic datasets, leading to numerous controversies surrounding their underlying mechanisms [8]. Consequently, improving the seismic resolutions and extracting the precise characterizations of these deep and intricate craton basin faults pose notable challenges [9]. Seismic attribute fusion has been at the forefront of innovations aimed at refining the accuracy and reliability of fault identification in subsurface exploration. Utilizing multiple attributes provides a comprehensive perspective, enhancing the clarity of fault systems within seismic datasets. In the Bakken Formation of the Williston Basin, North Dakota, principal component analysis of seismic attributes has been pivotal in discerning fault patterns, exemplifying the power of methodological integration for fault detection [10]. Additionally, merging multiple seismic attributes with advanced techniques like ant tracking and neural networks has been demonstrated to be particularly effective in fault detection, as highlighted in a study conducted in an Iranian oilfield [11]. The potential of multi-seismic-attribute analysis techniques in unveiling intricate fault configurations has also been evidenced in the southern Indus Basin, Pakistan, shedding light on previously obscured subsurface mysteries [12]. Furthermore, when analyzing structural complexities in compression-driven terrains, 3D seismic attributes play an indispensable role, as showcased in a study from the western Sichuan Basin [13]. The amalgamation of these methodologies underscores the rapidly evolving landscape of seismic exploration and the indispensable role of seismic attribute fusion in modern geophysics. At present, pinpointing attributes for deep strike-slip faults within cratons is still in its preliminary phase [9]. Notably, [PERSON] et al. (2019) made use of coherent volumes to detect strike-slip faults in the Tarim Basin, yielding significant outcomes in constructing a static model for hydrocarbon complex accumulation [14]. Similarly, [PERSON] et al. (2020) employed ant tracking attributes to map the Algeciras strike-slip fault in the Greater Llanos Basin, revealing the presence of WNW-ESE and NW-SE Riedel-type shear faults [15]. However, the characterization of strongly heterogeneous paleokast fracture-vuggy carbonate reservoirs controlled by strike-slip faults at depths of 7000-8000 m proves challenging solely through seismic attributes [16; 17]. A potential solution involves combining geophysical data, geological prior information, signal processing, and image fusion technology to establish a comprehensive and accurate identification method for deep strike-slip faults within cratons.