Origin of shallow gas in the Dutch North Sea - Seismic versus geochemical evidence

In the Dutch offshore, we have observed numerous acoustic anomalies, usually bright spots, in seismic data of Cenozoic deltaic deposits. When associated with shallow gas, these bright spots are good indicators of resource potential, drilling hazard, or seabed methane emissions. We apply a combined seismic and petrophysical assessment to qualify the bright spots as direct hydrocarbon indicators (DHIs) for shallow gas and to exclude alternative sources of seismic anomalies. In some cases, we use other DHIs such as flat spots, velocity push-downs, transmission, and attenuation effects as estimators for gas saturation. A long-standing discussion concerns the sourcing and migration of shallow gas. Although vertical seismic noise trails (chimneys) tend to be seen as proof that shallow gas originates from the migration of deeper sourced thermogenic gas, the geochemical and isotope analyses almost exclusively indicate that the gas is of microbial origin and generated in situ in the Cenozoic strata. We conclude that the observed “chimneys” are most likely transmission effects, that is, artifacts that do not represent migration pathways of gas. Hence, we believe that for the Dutch offshore, the presence of shallow biogenic gas is not indicative of leakage of deeper thermogenic petroleum plays and cannot be used as an exploration tool for these deeper targets.

Comprehensive detection device and physical testing for mechanical properties of seabed sediments and shallow gas

In this paper, a comprehensive detection device for the mechanical properties of seabed sediments and shallow gas is designed, which is mainly composed of the seabed sediment mechanical properties detection part, the shallow gas detection part and the ultrasonic wireless transmission part. The mud water gas separation structure of the shallow gas detection part separates the shallow gas from the mud water, and then the methane concentration in the shallow gas is measured by the non-dispersive infrared methane sensor, which realizes the collection of the submarine shallow gas and the automatic real-time monitoring of the concentration. The measurement of the mechanical properties of seabed sediments realizes the real-time measurement of the three parameters of cone resistance, sidewall friction and pore water pressure, which characterize the mechanical properties of seabed sediments, through strain-sensitive elements. The ultrasonic wireless data transmission part is mainly for the data detected by the mechanical properties of the seabed sediments to be wirelessly transmitted to the sensor placement room through the ultrasonic transducer across the mud-water-gas separation structure. Finally, the data measured by the two parts are transmitted to the mother ship through the cable located in the sensor placement room. The experimental results show that it has the ability to comprehensively detect the mechanical properties of seabed sediments and shallow gas, and has strong operability.

One Phase Well OPW : Unlock Shallow Reservoir Efficient and Economically by Eliminating Surface Casing

Tunu is a mature giant gas and condensate field locate in Mahakam Delta, East Kalimantan, Indonesia. The field has been in development for almost 30 years and currently has been considered as a mature field where to put a state of an economic well has become more challenging nowadays. The deeper zone of Tunu has no longer been considered as profitable to be produced and the current focus is more on the widespread shallow gas pocket located in the much shallower zone of Tunu. One phase well is architecture without 9-5/8" surface casing. OPW is one-section drilling using a diverter mode from surface to TD without using BOP. Historical for OPW is began from 2018, where drilling reservoir section using diverter mode in two-phase. In 2018 also succeeded in performing perforated surface casing. Due successfully in drilling operation using diverter and perforated surface casing, in 2019 drilling trials for OPW were carried out. Until now, the OPW architecture has become one of the common architecture used in drilling operations as an optimization effort. Until December 2020 PHM has completed 15+ OPW wells. A general comparison of OPW and SLA well is at the cost of constructing a well of approximately 200,000 - 300,000 US$. The disadvantages of OPW wells are more expensive in the mud and cement section when using a 9-1/2" hole, but in terms of the duration, OPW drilling time is more efficient up to 2-3 days. If viewed from the integrity of the OPW wells, from 15 OPW wells that have been completed, only 2 of them have SCP.

Casing While Drilling Level 2 as Mitigation for Shallow Gas and Loss Circulation Hazards in Surface Section

Casing while drilling Level 2 was introduced to mitigate problems in the surface section of Mutiara and Pamaguan Field in East Kalimantan. These two fields have historical shallow gas and loss circulation hazards in surface section. Following a blowout incident in Pamaguan in 2012, new policy was introduced for drilling the surface section in Mutiara and Pamaguan. A pilot hole must be drilled, and additional surface casing shall be set. Although considered safe, longer drilling days and vulnerability to repeated loss circulation made this method inefficient. A new approach to mitigate the problem was proposed by introducing casing while drilling Level 2 in 2020 drilling campaign. Many papers already discussed about the effectiveness of casing while drilling to mitigate loss circulation. However, a limited number of papers discuss casing while drilling to mitigate shallow gas. Costeno et al, 2012, discussed the use of casing while drilling to mitigate shallow gas. However, the risk of shallow gas was low and there was no shallow gas record during the execution. This paper specifically discusses about utilizing casing while drilling (CWD) technology to mitigate not only loss circulation, but also shallow gas risks during surface hole interval. Both hazards occurred in several wells during job execution and CWD with its plastering effect has managed to drill troublesome surface hole safely, thus making it the better alternative to achieve efficient drilling in comparison with the previously used pilot hole method.

First Application Drilling New Wells with HWU in Swamp Environment, Mahakam Delta

Tunu is a mature giant gas and condensate field locate in Swamp Area on Mahakam Delta, East Kalimantan, Indonesia. The field has been in developed for more than 40 years and considered as a mature field. As mature field, finding an economic well has become more challenging nowadays. The deeper zone of Tunu (TMZ) has no longer been considered profitable to be produced and the focus is shifted more on the producing widespread shallow gas pocket located in the much shallower zone of Tunu (TSZ). Facing the challenge of marginal reserves in the mature field, Pertamina Hulu Mahakam (PHM) take two approaches of reducing well cost thus increase well economics, improving drilling efficiency and alternative drilling means. Continues improvement on drilling efficiency by batch drilling, maxi drill, maximizing offline activities and industrialization of one phase well architecture has significantly squeezed the well duration. The last achievement is completing shallow well in 2.125 days from average of 6.5 days in period of 2017-2019. Utilization of Swamp Barge Drilling Rig on swamp area had been started from the beginning of the field development in 1980. Having both lighter and smaller drilling unit as alternative drilling means will give opportunity of reducing daily drilling rate. Hydraulic Workover Unit (HWU) comes as the best alternative drilling means for swamp area. In addition, fewer and smaller footprint equipment requires smaller barges with purpose of less civil works to dredge the river and preparing well location. Drilling with HWU project has been implemented at Tunu area with 5 wells has been completed successfully and safely. HWU drilling concept considered as proven alternative drilling means for the future of shallow wells development.

Machine Learning Technology to Improve Precision and Accelerate Screening Shallow Gas Potentials in Tunu Shallow Gas Zone, PT Pertamina Hulu Mahakam

Tunu is a giant gas field located in the present-day Mahakam Delta, East Kalimantan, Indonesia. Tunu gas produced from Tunu Main Zone (TMZ), between 2500-4500 m TVDSS and Tunu Shallow Zone (TSZ) located on depth 600 - 1500 m TVDSS. Gas reservoirs are scattered along the Tunu Field and corresponds with fluio-deltaic series. Main lithologies are shale, sand, and coal layers. Shallow gas trapping system is a combination of stratigraphic features, and geological structures. The TSZ development relies heavily on the use seismic to assess and identify gas sand reservoirs as drilling targets. The main challenge for conventional use of seismic is differentiating the gas sands from the coal layers. Gas sands are identified by an established seismic workflow that comprises of four different analysis on pre-stack and angle stacks, CDP gathers, amplitude versus angle(AVA), and inversion/litho-seismic cube. This workflow has a high success rate in identifying gas, but requires a lot of time to assess the prospect. The challenge is to assess more than 20,000 shallow objects in TSZ, it is important to have a faster and more efficient workflow to speed up the development phase. The aim of this study is to evaluate the robustness of machine learning to quantify seismic objects/geobodies to be gas reservoirs. We tested various machine learning methods to fit learn geological Tunu characteristic to the seismic data. The training result shows that a gas sand geobody can be predicted using combination of AVA gather, sub-stacks and seismic attributes with model precision of 80%. Two blind wells tests showed precision more than 95% while other final set tests are under evaluated. Detectability here is the ability of machine learning to predicted the actual gas reservoir as compared to the number of gas reservoirs found in that particular wells test. Outcome from this study is expected to accelerate gas assessment workflow in the near future using the machine learning probability cube, with more optimized and quantitative workflow by showing its predictive value in each anomaly.