Regional Suitability Mapping (PRSM) was initiated in 2013 with the aim of optimizing operational cost efficiency, minimizing potential incidents during jack-up emplacement and assist in planning for rig selection. This paper will highlight the performance of jack up rig leg penetration prediction using PRSM for Offshore Malaysia.
PRSM comprises data analysis and integration from various sources such as geotechnical and geophysical site investigation data and data from rig entries. These data sets are then uploaded to a web-based Geographic Information System (GIS). The jack up rig leg penetration range predicted from PRSM GIS database is then compared to the actual jack up rig leg penetration. A comparison to the calculated jack up rig leg penetration was also made and the differences between these results are postulated.
A total of 23 recent jack up entry sites has been chosen randomly, which comprises 8 locations in Offshore Peninsular Malaysia, 12 locations in Offshore Sarawak and 3 locations in Offshore Sabah. The expected leg penetration at these locations were acquired from PRSM GIS. Results show that 75.0% of the sites in Offshore Peninsular correlate with the prediction range from PRSM GIS while only 27.3% of the sites in Offshore Sarawak correlate with the prediction range. For Offshore Sabah, all the locations correlate with the prediction range obtained from PRSM GIS. Results from predicted spudcan penetration calculated based on ISO 19905-1 (2016) against the actual penetration results show that 87.5% of the sites in Offshore Peninsular falls in between the ±10% reference band while 63.6% of the sites in Offshore Sarawak falls in between the ±10% reference band. However, none of the sites in Offshore Sabah falls in between the ±10% reference band. Findings from this exercise indicates area in Offshore Sarawak consist of two different features. Firstly, there are locations with thick sand layer close to seabed associated with shallow penetration of spudcans. Secondly, locations with presence of homogeneous clays with linearly increasing strength associated with deeper penetration of spudcans. Moreover, the available data around Offshore Sarawak field are scattered between one another, which leads to bigger data gaps. The shallow leg penetrations in Offshore Sabah are associated with the presence of coral and/or sand close to seabed.
This paper aims to showcase the use of big data and GIS to help in jack up leg penetration predictions hence optimizing the operational cost efficiency, minimizing potential incidents during jack-up emplacement.