Mature fields contain wells drilled over decades, resulting in a complex distribution of cased hole from active producers, injectors, and abandoned wells. Continued field development requires access to bypassed pay and the drilling of new wells that must be threaded between the existing subterranean infrastructure. It is therefore important to know the position of any offset wells relative to a well being drilled so collision can be avoided. A well’s position is determined by directional survey points, for which the measurement error accumulates along the length of the well, increasing the uncertainty associated with the well position. The positional uncertainty is greater in wells drilled with older generations of surveying tools. Thus, a new well may be required to enter the ellipse of uncertainty representing the potential position of an older well, risking collision, to be able to reach desired targets in more distal parts of the reservoir. A potential solution to reduce collision risks is ultra-deep electromagnetic (EM) logging-while-drilling (LWD) tools, whose measurements are strongly influenced by proximity to metal casing and liners. This paper presents 3D inversion results of ultra-deep EM data from a development well in a mature field, which were used to identify a nearby cased well. Due to the large effect of casing on the measured EM field, it is important to validate the 3D results; this has been achieved using a synthetic modelling approach and assessment of azimuthal EM measurements. Models were created with casing positioned within resistive media with similar properties to those seen in the studied cases. Inverting these models allows testing of the inversion algorithm to show that it is providing a good representation of the cased well’s position relative to the newly drilled well. Further analysis of recorded and synthetic data showed that the raw EM field is strongly influenced as the casing is approached. The casing can be seen to clearly affect the EM field measurements when it is in the region of 10 to 15 m ahead of the EM transmitter, with the effect increasing in magnitude as this distance diminishes. Modelling shows that the EM field measurements behave in a predictable manner. As the ultra-deep EM tool approaches a cased well, it is possible to determine whether the casing is above, below, or critically, directly in line with the planned trajectory of the new well. Existing subterranean infrastructure can pose a major hazard to the drilling of new wells. Being able to identify an old well ahead of the bit using ultra-deep EM measurements would allow a new well to be steered away from the hazard or drilling stopped, preventing a collision. In addition, this may also allow the drilling of well paths that would otherwise be impossible to drill, due to the limitations imposed by positional uncertainty of the new and offset wells. This use of ultra-deep resistivity technology takes it beyond its more traditional benefits in well placement and formation evaluation, making it useful for improving well drilling safety.
The gas present in the Valhall overburden crest area interferes with the seismic data and obscures the fault detection (minor faults). Spatially resolving fractures and fracture network is essential for subsurface understanding and future well placement in this field, and it is a critical input to the dynamic reservoir model. Additionally, mapping the fracture network in poor permeable reservoir formation beyond the wellbore is crucial to identify completion intervals to maximize productivity/injectivity, and hence field value. The well 2/8-F-18 A was drilled on the crest of the Valhall field as a pilot water injector in Lower Hod formation, where core and data analysis formed the foundation for a future potential 11 well development. The well is placed in the southern section of the Valhall crest, and no major faults or strong amplitude features were mapped out in the overburden via surface seismic before drilling. In this case study, an integrated workflow is proposed and tested within the reservoir formation to identify “sweet” (permeable and fractured) zones beyond the wellbore. This is achieved using borehole acoustic data combined with image and ultrasonic imaging to characterize fracture networks beyond the borehole wall. The sonic imaging workflow identifies reflection events from fractures and faults and provides the true dip, azimuth, and location in 3-dimensions. This data is complemented by nuclear magnetic resonance (NMR), dielectric and spectroscopy data to understand reservoir petrophysics. NMR-derived permeability has also been evaluated for identifying high permeable zone in this formation, which primarily focuses on intergranular permeability of the formation a few inches away from the borehole wall. Reservoir textural heterogeneity and fractures beyond the wellbore wall make this method difficult to estimate or enhance the effective permeability estimate. The baseline assumption for the NMR permeability estimation is also not valid in Hod formation; the Timur and SDR equation needs significant change to match core permeability. Hence, the primary aim is to identify a fracture network that will help support water injection and maximize hydrocarbons production through them. The goal is to establish a workflow from the learnings of this study, performed on the pilot well, validate its findings with the near-field data (core, imaging, and ultrasonic), and optimize it if needed (described in the methodology section). The developed workflow is then intended to be used to optimize the placement of future wells. The results achieved from the integrated workflow identified a key fault and mapped it approximately 23 meters away on each side of the borehole. It also captures acoustic anomalies (high amplitudes), validated based on near-field data, resulting from a fracture network potentially filled with hydrocarbons. The final results show the sub-seismic resolution of the fracture and fault network not visible on surface seismic due to the gas cloud above the reservoir and frequency effect on the surface seismic when compared to borehole sonic data. Evidently enhancing the blurred surface image, which helps enhance the structural and dynamic model of the reservoir.
The Ivar Aasen (IA) oilfield is located on the Gudrun Terrace on the eastern flank of the Viking Graben in the Norwegian North Sea. The field was discovered in 2008. The reservoir is located within a sedimentary sequence of Mid-Jurassic to Late-Triassic age, which consists of shallow marine to fluvial, alluvial, floodplain and lacustrine deposits overlying a regionally extensive, fractured calcrete interval. The sequence exhibits a complex mineral composition and is heterogeneous at a scale below that of a logging sensor. Shale layers, re-deposited shale and what was first believed to be redeposited calcrete fragments present in various forms throughout the sequence. Looking more in depth to XRD and XRF data and contrasting Fe concentration in the dolomite, it is also possible to explain some of the carbonate deposits through other processes. Extensive data acquisition in the form of advanced wireline logs and coring with analysis performed in “geopilot” wells before production start, enabled a novel thin bed formation evaluation technique based on the modified Thomas-Stieber method (Johansen et al. 2018). The method increased the in-place oil volumes within the Triassic reservoir zone internally named Skagerrak 2. This led to several improvements and a modified drainage strategy of Ivar Aasen. Several good producers were placed in the complex net of the Skagerrak 2 Formation. Results from these producers have encouraged development of an even more marginal and complex net, deeper into the Triassic sedimentary sequence. Therefore, another “geopilot” was drilled into the deeper Triassic sediments, internally named as the Alluvial Fan. This zone exhibits conglomerate clasts in a matrix varying between clay, silt, feldspars, and very fine to very coarse sand fractions, grading towards gravel. Previously, this zone was considered to be mostly non-net. Applying the same interpretation method as for Skagerrak 2, the Alluvial Fan promised economic hydrocarbon volumes. The latest geopilot proved producible hydrocarbons, and subsequently a producer was also successfully placed in this part of the reservoir. Production data and history matching from the beginning of production have for a long while established the previous increase of IA Triassic oil volumes published in 2018. Advanced studies of mineralogy and spectroscopy (Johansen et al. 2019) have indicated that a significant amount of the previously interpreted dolomite, could be reinterpreted as ferroan dolomite. The latter is a heavier mineral that increases the matrix density, hence also the total porosity. The additional findings described provided another necessary first-order correction to further enhance the evergreen geomodel. This paper describes this methodology which resulted in improved petrophysics and reservoir properties of the Alluvial Fan, yet again demonstrating the value of advanced wireline logs and detailed analysis that in total impacts the IA reserve volumes in a significant manner. Repeated success with the applied spectroscopy data and the thin bed methodology used today (Johansen et al. 2018), has resulted in even the deeper Braid Plain Formation becoming of economic interest. It is expected to lie within the oil zone in an upthrow block in the northern part of the IA field and could be developed into the next target.
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