Reverse-time modeling of channelized meandering systems from geological observations

Marion Parquer. ( 2018 )
Universit{\'e} de Lorraine

Abstract

Meandering systems constitute the majority of aerial and sub-marine rivers which shape the landscapes by their temporal and spatial evolution. The witnesses of this evolution can be observed on the plains crossed by these channels. Among them, lateral point bar resulting from the channel migration but also abandoned meanders created by the natural stream rectifying and abandoned channels originating from the main direction change by avulsion. Once buried, the channelized systems are good candidates for natural resources storage thanks to the diversity and the volume of the resulting deposits. The understanding of the internal architecture of facies is thus crucial for resource exploitation. Satellite and LIDAR images permit current system studies. Subsurface architecture can be imaged by seismic images, GPR or LIDAR. These techniques give a good evaluation of the system last channel path. However, anterior stages, when spared by the erosion can be observed locally. Indeed, the reworking of the channel belt by lateral and downstream migration makes it difficult to observe the geometric or chronologic features of anterior deposits. This thesis proposes a simulation method of channelized systems conditioning to available information. Among them, the seismic image often permits to identify the last system stage and the abandoned meanders thanks to their muddy filling after the abandonment time contrasting with the channel belt. Lateral point bars can also be observed, witnessing of meander paleo-migration direction. Sometimes, well data inform on the facies (e.g., muddy, sandy). The method presented here starts from the last channel path observed on the seismic image and go back in time by reverse migration to reconstruct anterior channel paths. This stochastic migration model is inspired by the analysis of historic Mississippi maps. According to a chronology simulation based on spatial and statistical criteria (e.g., distance and orientation to the current channel, abandonment probability distribution), abandoned meanders are integrated at the relevant time step inside the main channel path. Erosion of abandoned meanders is addressed by abandoned meander simulation inside the meander belt. This stochastic simulation conditions to geometrical criteria observed on the abandoned meanders spared by the erosion but also to statistical criteria observed on sedimentary analogs such as the Mississippi river (e.g., erosion probability distribution). One of the main perspectives is to condition to well data through the simulation of abandoned meanders. This technique has been applied on two satellite and seismic 2D case studies

Download / Links

BibTeX Reference

@phdthesis{parquer:tel-01902547,
 abstract = {Meandering systems constitute the majority of aerial and sub-marine rivers which shape the landscapes by their temporal and spatial evolution. The witnesses of this evolution can be observed on the plains crossed by these channels. Among them, lateral point bar resulting from the channel migration but also abandoned meanders created by the natural stream rectifying and abandoned channels originating from the main direction change by avulsion. Once buried, the channelized systems are good candidates for natural resources storage thanks to the diversity and the volume of the resulting deposits. The understanding of the internal architecture of facies is thus crucial for resource exploitation. Satellite and LIDAR images permit current system studies. Subsurface architecture can be imaged by seismic images, GPR or LIDAR. These techniques give a good evaluation of the system last channel path. However, anterior stages, when spared by the erosion can be observed locally. Indeed, the reworking of the channel belt by lateral and downstream migration makes it difficult to observe the geometric or chronologic features of anterior deposits. This thesis proposes a simulation method of channelized systems conditioning to available information. Among them, the seismic image often permits to identify the last system stage and the abandoned meanders thanks to their muddy filling after the abandonment time contrasting with the channel belt. Lateral point bars can also be observed, witnessing of meander paleo-migration direction. Sometimes, well data inform on the facies (e.g., muddy, sandy). The method presented here starts from the last channel path observed on the seismic image and go back in time by reverse migration to reconstruct anterior channel paths. This stochastic migration model is inspired by the analysis of historic Mississippi maps. According to a chronology simulation based on spatial and statistical criteria (e.g., distance and orientation to the current channel, abandonment probability distribution), abandoned meanders are integrated at the relevant time step inside the main channel path. Erosion of abandoned meanders is addressed by abandoned meander simulation inside the meander belt. This stochastic simulation conditions to geometrical criteria observed on the abandoned meanders spared by the erosion but also to statistical criteria observed on sedimentary analogs such as the Mississippi river (e.g., erosion probability distribution). One of the main perspectives is to condition to well data through the simulation of abandoned meanders. This technique has been applied on two satellite and seismic 2D case studies},
 author = {Parquer, Marion},
 hal_id = {tel-01902547},
 hal_version = {v1},
 keywords = {Channelized system ; Abandoned meander ; Stochastic simulation ; Sedimentary record ; Syst{\`e}me chenalis{\'e} ; Migration ; M{\'e}andre abandonn{\'e} ; Simulation stochastique ; R{\'e}servoir ; Enregistrement s{\'e}dimentaire},
 month = {April},
 number = {2018LORR0081},
 pdf = {https://hal.univ-lorraine.fr/tel-01902547/file/DDOC_T_2018_0081_PARQUER.pdf},
 school = {{Universit{\'e} de Lorraine}},
 title = {{Reverse-time modeling of channelized meandering systems from geological observations}},
 type = {Theses},
 url = {https://hal.univ-lorraine.fr/tel-01902547},
 year = {2018}
}