## 1 Introduction  
The development of a new class of automated fault detection and extraction under Gas Chimneys is a key step in the development of a new class of automated fault detection and extraction  
## 1 Introduction  
Our Earth is dynamic and tectonic forces reshape it over time. A fault is one of the most notable features in subsurface manifesting these complex forces at work. Sound understanding and interpreting the fault system accurately is crucial to any hydrocarbon exploration and development project's success. With the more frequent availability of 3D-Seismic data, fault interpretation has become more challenging and a tedious job. Moreover, seismic data are often immersed in noise, which makes it difficult to extract useful structural and stratigraphic information. Therefore, traditional fault picking not only becomes challenging but also time-consuming and error-prone. Manual interpretation becomes even more cumbersome when it comes to interpreting smaller discontinuities that are difficult to resolve by seismic data. Automated picking constrained by discontinuity attributes is needed to overcome these challenges. Many researchers have worked on the development of discontinuity or its inverse, seismic continuity attributes, to better visualize and interpret seismic objects. For example, cross-correlation [1], semblance [2], similarity [3], variance [4], and eigenstructure [5; 6]. In the available literature, a lot of work has been carried out using individual seismic attributes and filters. If attribute selection is not made carefully, the analysis may yield poor and unsatisfactory results, especially when applied by a novice [7]. A more thoughtful and integrated approach could improve the results significantly. Therefore, our aim is to device a multistep workflow to blend the seismic attributes considered best to capture and optimize the discontinuities, and then use them to extract faults in an automatic manner. The aspects of [PERSON]'s novel approach on automated fault detection and extraction have been integrated in our hybrid workflow. In the context of exploration geophysics, fault dip and strike angles are the main components to illustrate the faults on the outcrop and in the subsurface (Figure 1). Fault throw is a critical parameter that describes the movement of strata that is perpendicular to the strike of a fault. Fault orientation and its throw vary along fault planes in most cases. Fault throw relative to the dip of a fault is usually more significant than displacement along the strike of a fault. Moreover, fault throw vectors are usually more perpendicular to geologic layers, and are therefore easier to estimate than strike-slip displacements, according to [8; 9; 10] [PERSON]. However, if there is an insignificant fault throw or minor discontinuities, the traditional fault detection method based on coherency fails to produce satisfactory results. To fully address such composite scenarios, we chose to use a hybrid workflow and incorporated multiple discontinuity attributes. Pre-conditioning of the noisy seismic data, being the first step, is the most important and critical step of the workflow. An essential task is to improve reflector continuity, enhance resolution for better imaging and increase  
Figure 1: **(a)** Fault dip represents displacement in the dip direction with respect to a hanging wall whereas fault throw is the vertical component of the slip. Panel (**b**) shows the fault strike and dip angles with their respective unit vectors [9]. (Reproduced with permission from [PERSON], Geophysics, published by SEG, 2016). the signal-to-noise ratio (S/N) for seismic data interpretation. This step is of particular importance because the seismic data used in this study is moderate to intensely faulted and is marred with gas chimneys [11; 12]. The structure is sagging, and reflector's continuity has been heavily compromised due to the chimney effect.