Use this URL to cite or link to this record in EThOS:
Title: Seismic history matching using binary images
Author: Obidegwu, Dennis
ISNI:       0000 0004 7963 4590
Awarding Body: Heriot-Watt University
Current Institution: Heriot-Watt University
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Access from Institution:
The ability to predict the flow of multiple fluids in a reservoir, and update the reservoir in a timely efficient manner is the dream of every reservoir engineer, and has been the bane of much research in the oil and gas industry. This is highly sought after because it enables efficient reservoir monitoring, management and planning. However this requires some level of skill and precision as well as the ability to interpret and input data from different sources into the model. In order to predict the flow of multiple fluids in a reservoir, the relative permeability of these fluids has to be determined. In this thesis, 4D seismic data is used to estimate some endpoints of the relative permeability curve (Sgc and Sgmax), whereby multiple seismic surveys are employed in association with the production history, depletion mechanism, geological and structural effects as well as reservoir simulation predictions. The multiple survey 4D seismic data is interpreted so as to decipher instances of critical gas saturation as well as maximum gas saturation effects, these are then quantitatively analysed, and a relationship between the ratio of their amplitudes and gas saturation are used to estimate the values. In addition, integrating 4D seismic data with production data in a quantitative manner in a reservoir model improves the model's capability and reduces the uncertainty, however doing this is quite a challenging problem. This thesis addresses this challenge by utilising a binary approach which circumvents the full rock physics modelling approach. The binary approach is developed and tested where gas and water saturation from 4D seismic data and the reservoir simulation model are converted to binary indicators. Different metrics for quantifying the binary misfit in terms of their strengths and short comings are analysed, and the Current measurement metric and Hamming distance exhibit better capabilities than the Hausdorff distance and Mutual Information measurements. The binary approach is then tested on a synthetic model in order to validate its use, as well as show its functionality in a practical setting. In the synthetic study, three different scenarios are analysed - the gas exsolution scenarios, the water evolution scenarios, and a combination of gas exsolution and water evolution, and the results show that the binary approach provides a quick and efficient method of assessing reservoir parameters. The binary approach is then implemented on a real field data from the United Kingdom Continental Shelf (UKCS), where 104 uncertain reservoir parameters are initially assessed. An initial ensemble of fluid flow simulation models is created where the full range of uncertain parameters are acknowledged using experimental design methods, and an evolutionary algorithm is used for optimization in the history matching process. It is found that the primary control parameters for the binary seismic gas match are the permeability and critical gas saturation, while the volumetric parameters are important for the binary seismic water match in this particular reservoir. This binary approach is then compared to a conventional seismic modeling approximation approach, where the results show that the binary approach gives a good match to gas saturation distribution and water saturation distribution, and the reservoir parameters converge towards a solution. The conventional approach captures some signals of hardening and softening in the seismic data, however most parameters do not fully converge towards a solution, and hence in summary, the binary approach seems more suitable as a quick look reservoir management tool.
Supervisor: MacBeth, Colin Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available