Most conventional logging-while-drilling (LWD) tools acquire real-time measurements from a few inches to a few feet away from the wellbore for lithology, porosity, and saturation evaluation. Deep and ultra-deep resistivity tools were developed primarily for well placement and geomapping applications and can detect resistivity variations further away, in all directions around the wellbore. This article describes integration of deep and ultra-deep resistivity measurements for saturation mapping beyond the wellbore. Deep and ultra-deep resistivity tools can map multiple formation layers and determine the resistivity of those layers far from the wellbore. Since saturation is dependent on porosity and resistivity, a workflow has been developed to combine real-time shallow measurements with inverted LWD resistivity measurements and logging data from offset wells. The geological model is updated based on deep resistivity measurements, and petrophysical parameters for each layer, combined with inverted resistivity values, are used to derive saturation. Uncertainty is defined based on weighted uncertainty in porosity from offset wells and variation in resistivity across the mapped layers. Azimuthal resistivity measurements were also used to validate the inverted values and reduce uncertainties in cases of boundaries close to the wellbore. The workflow has been tested on several wells and different reservoirs. Several wells were presented in this study utilizing a combination of shallow and deep azimuthal data along with offset logs. Different layers of different formation characteristics and saturation profiles have been crossed and the data was utilized to validate the mapped saturation values compared to the nearby measurements. The resulting saturation profile provided critical information that enhanced understanding of the reservoir and gave better insight into variation in the far field. Such information is critical for completion-design and well-placement decisions and aligns with the industry's direction toward increased data analytics combining offset wells with real-time data. A continuous improvement of the model is expected as more wells are drilled and the database increases.
Conventional logging-while-drilling tools acquire measurements close to the wellbore. Recent development of deep and ultra-deep resistivity technology has enabled measurements more than 100 ft from the wellbore. Far-field petrophysics in simple carbonate lithology is possible since saturation is dependent on resistivity and porosity. Hence, combining deep and ultra-deep resistivity measurements with data from offset wells can provide reasonable saturation mapping. However, in clastics the evaluation is more complicated since resistivity is more dependent on lithology. In most cases, the main challenge in carbonates is permeability identification. Far-field carbonate petrophysics can be derived from mapped resistivity utilizing deep or ultra-deep resistivity and offset logs. Evaluation of far-field petrophysics away from the wellbore in clastics is more complicated as it requires lithology identification to be incorporated into the petrophysical model. A workflow has been developed integrating near-wellbore measurements with ultra-deep resistivity and anisotropy derived from 3D inversion. The workflow provides a qualitative indication of the lithology, allowing saturation in porous sand to be derived based on inverted resistivity. An innovative workflow has been developed based on the available data and combining multiple sources of data from near wellbore, offset logs to inverted resistivity data. 3D inversion plays a critical role in this workflow as it provides a lithology indication far away from the wellbore, differentiating between shale and sand. The identification of shale members at a distance also provides critical information for models of reservoir connectivity and potential barriers to water influx. The combination of far-field petrophysics with lithology gives better evaluation on a reservoir scale for critical decisions in terms of completion and reservoir performance. The new workflow has been successfully tested on several wells and different reservoirs. The workflow has been used for far field petrophysics and saturation mapping based on real-time logging-while-drilling (LWD) data and offset data analysis combining shallow and deep measurements with the 3D inversion from ultra-deep resistivity. There are several benefits from this innovative workflow, including optimizing well placement, improving understanding of fluid distribution, and optimizing completions design and reservoir management strategies.
Proper reservoir evaluation in carbonate and sandstone environments has always been a challenge. Petrophysicists are constantly struggling with water salinity uncertainty and Archie's exponents (m and n). These parameters are often not readily available, require time-consuming special core analysis and can vary significantly within and across depositional sequences. A new generation of dielectric technology, which provides reliable measurements that overcomes some of the limitations of the old devices, is used. The enhanced data from the tool improves petrophysical formation evaluation in a variety of borehole environments.Measurements from dielectric devices have been available via wireline conveyance for more than three decades. Several devices operating with a single-frequency were built in the eighties. Most failed to gain acceptance due to measurement limitations affected by borehole and invasion effects, and moderate accuracy making their interpretation complicated. Based on recent technology developments, a new device measuring both permittivity and conductivity at multiple frequencies has enabled petrophysicists to evaluate the petrophysical properties in various complex environments.The combination of dielectric with other conventional logging measurements had been utilized in many wells to determine water saturation and remaining hydrocarbon saturation on a regular basis. In addition, the continuous variable Archie's exponent "MN" measurement from dielectric is used to estimate accurately water saturation. The difference in volume of total porosity and the dielectric quantification of water filled porosity (WFP) is used to estimate hydrocarbon saturation. A new approach for identifying and quantifying gas thinly bedded sands is tested with promising results. It combines high resolution dielectric measurements, borehole images and nuclear magnetic resonance (NMR) measurements. Integration of dielectric data to the conventional open-hole logging suites enables rapid and accurate results during the logging operation and allows proper decisions on pressure points to optimize logging time and reduce substantial cost.Saudi Aramco has been leading the tests of the technology in a diverse range of environments and for various applications. The development and theory behind the dielectric measurements are discussed. Examples highlighting the value of these new measurements for improved formation evaluation in both carbonate and sandstone environments are provided in the paper.
The main objective was to drill a power water horizontal injector within the sweet spot of a thin fractured and heterogeneous reservoir to achieve pressure stabilization in this producing field and an optimized sweep at the bottom of reservoir to maximize and prolong production. A traditional triple-combo logging while drilling (LWD) portfolio cannot fulfill these challenging reservoir navigation and formation evaluation (FE) objectives simultaneously because of the limited number of measurements. Hence, a more holistic approach is required to optimize the well placement via the integration of real-time LWD FE measurements to maximize the injectivity. An integrated LWD assembly was utilized and offset well FE data were studied to select the best zone for well placement to provide the best injectivity and production of the remaining oil towards the base of the reservoir. Extensive pre-well modeling was performed, based on offset well data with multiple scenarios reviewed to cover all eventualities. Another challenge was to place the wellbore in a relatively low resistive zone (water wet) in contrast to normal development wells where the wellbore is navigated in high resistive hydrocarbon bearing zones, so conventional distance to bed boundary mapping methodology was not applicable. To overcome this challenge; advanced Multi Component (MC) While Drilling resistivity inversion was proposed in conjunction with deep azimuthal resistivity technology. The benefit of this technique is in providing the resistivity of each layer within the depth of detection along with thickness and dip of each layer. Resistivity inversion results were correlated with nuclear magnetic resonance (NMR) porosity and volumetric data to identify the best zone for well placement. As MC inversion was able to map multiple layers within ~7 ft radius depth of detection, changing thicknesses and dip of each layer; the geosteering team was able to make proactive recommendations based on the inversion results. These proactive trajectory adjustments resulted in maintaining the wellbore within a thin target zone (1-3 ft in thickness) also confirmed by NMR and Formation Testing Service (FTS) in real-time, achieving excellent net-to-gross, which otherwise would not have been possible. The hexa-combo LWD assembly supported optimum well placement and provided valuable information about the geological structure through the analysis of high-resolution electrical images identifying the structural events which cause compartmentalization, confirmed by FTS results. This integrated LWD approach enabled proactive well trajectory adjustments to maintain the wellbore within the optimum porous, permeable and fractured target zone. This integrated methodology improved the contact within the water-injection target of the horizontal section, in a challenging thin reservoir and achieved 97.5 % exposure. Using an integrated LWD hexa-combo BHA and full real-time analysis the objective was achieved in one run with zero Non-Productive Time (NPT) and without any real-time or memory data quality issues.
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