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Resistivity is the one of the most difficult formation parameters to measure accurately because of the complex changes that occur during and after drilling a well and that may still be occurring during logging. The various components of the downhole environment may have strongly contrasting resistivities, some of which cannot be measured directly, and their physical dimensions may not be readily available. Figure 1 shows an idealized relationship of the main environmental components. There is no direct measurement of Rt. It must be inferred from the multiple-depth resistivity measurements.
One role of the petrophysicist is to characterize the fluids encountered in the reservoir. Detection of a change in fluid type in the rocks while drilling is usually straightforward with the use of gas and chromatographic measurements. Gas shows and oil shows while drilling are time-honored indicators of zones that need further investigation through logs, testers, and cores. In the rare case of gas-bearing, high-permeability rock drilled with high overbalance, gas will be flushed from the rock ahead of the bit, will not be circulated to the surface in the mud, and will not produce a gas show. Because hydrocarbons are not always part of a water-based-mud formulation, sophisticated analytical chemical techniques can be used on the oil and gas samples circulated to the surface and captured to determine the properties of hydrocarbons in a given zone penetrated by the drill bit.
The electromagnetic-wave resistivity (EWR) tool has become the standard of the logging while drilling (LWD) environment. Historically the earliest LWD electromagnetic measurements were Toroidal ( The Arps system of the 1960's [1]) and Short Normal and Laterolog measurements [2] of the late 1970's Exlog systems. However technical and mechanical survival considerations quickly caused the 2 Mhz systems to dominate, and these were then expanded with other frequencies.The nature of the electromagnetic measurement requires that the tool typically be equipped with a loop antenna that fits around the OD (outer diameter) of the drill collar and emits electromagnetic waves between slots of a steel protective shroud, which enables a robust mechanical design. The waves travel through the immediate wellbore environment, and are detected by a pair of receivers. Two types of wave measurements are performed at the receivers.
Capillary pressure and relative permeability are essential measurements that affect multiphase fluid flow in porous media directly. The processes of measuring these parameters, however, are both time-consuming and expensive. Artificial-intelligence methods have achieved promising results in modeling extremely complicated phenomena in the industry. In the complete paper, the authors generate a model by using an artificial-neural-network (ANN) technique to predict both capillary pressure and relative permeability from resistivity. Capillary pressure and resistivity are two of the most significant parameters governing fluid flow in oil and gas reservoirs.
Electromagnetic (EM) inversion processing of ultradeep resistivity data has advanced from one dimensional (1D) to three dimensional (3D). These advances have helped improve the geological complexity that can be imaged and provide additional reservoir information. The large depth of investigation (DOI) of ultradeep LWD EM tools means that distant boundaries might not be detected by any other sensor in the tool string, making it difficult to verify the results. As inversion results represent a model of the subsurface resistivity distribution and not a direct measurement, it is important to have high confidence in the results. Directly comparing the component data measured by the tool to the modeled component data from the inversion across multiple frequencies provides confidence in the resultant model where the data have a close fit. However, as measurement sensitivities decrease with distance, there is potential for non-uniqueness, generating a model that is geologically unrealistic. Increased confidence can be achieved with independent verification of the model. This paper details results from a trilateral well in an injectite reservoir wherein the sand distribution was expected to be complex. The 1D inversions showed the vertical distribution of the sand, but the results were sometimes distorted by lateral resistivity variations. The 3D inversion of the data allowed the lateral resistivity variations to be resolved. These results can be corroborated by direct comparison with azimuthal resistivity images. Additionally, the laterals all diverged from the same main bore and remained close together initially in an area containing major sand injectites. The 3D inversions from two of the wells overlap and define similarly shaped structures, providing confidence in the 3D inversion model. In complex geobodies, such as the injectites described, significant lateral variation in the reservoir distribution is expected, which is not captured by 1D inversion. Understanding the shape of these structures and their potential connectivity using 3D inversion provides a major increase in reservoir understanding that is critical to completion design.
In this paper, we examine fluids interpretation techniques in a prolific oil field in offshore West Africa. A sourceless logging program, consisting of logging-while-drilling (LWD) nuclear magnetic resonance (NMR), resistivity, and formation tester, was chosen to log the reservoir section in 6.5-in. holes. The purpose of this study is to answer questions related to asset appraisal and development with these limited measurements. Core data available are porosity, permeability, water salinity, Archie m and n, and Dean-Stark Sw. A comparison of the core and NMR log indicates that NMR total porosity is not affected by hydrocarbon in the pore space. We use a statistical method called factor analysis to deconvolve independent fluid modes from the T2 distribution and pick the T2 cutoff. The NMR irreducible water saturation (Swirr) computed with this cutoff agrees with Dean-Stark Sw. Continuous Sw is calculated with Archie’s equation with lab-measured parameters and validated against Dean-Stark Sw above the transition zone. The Timur-Coates model is used to estimate matrix permeability. The first application of this interpretation workflow is to confirm the free-water level (FWL) derived from pressure gradients. We found the Sw profile largely controlled by heterogeneity in rock textures. The presence of both good and poor-quality rocks makes log-based FWL picking difficult. We use Swirr from NMR to indicate rock quality and simplify our final interpretation. The FWL found by sourceless log interpretation is consistent with the initial FWL found by pressure gradients. The second application is perforation design. Zones with good porosity and low mobile water volume are selected for perforation, and a safe distance is maintained from FWL. As a result, all producer wells exhibit zero water cut.
If the pillars of industry such as wisdom, truth, commitment, and character could talk to the generation of young professionals about to inherit the oil and gas industry, the world's energy future would definitely be a bright one. The oil and gas industry contains some of the brightest, most innovative, and most dedicated people who practice in any profession, but the time is coming when they will have to open the door for the next generation. The great crew change is coming, and the benefit from the exchange of knowledge and advice between the two generations is invaluable. The Pillars of Industry section of The Way Ahead will focus on individuals who have established or distinguished themselves as pillars in the oil and gas industry. They will present their field of experience from a mentorship perspective. The authors will introduce their career and field of expertise, with emphasis on career advice for success in the industry.
This paper discusses ultradeep directional-resistivity (DDR) logging-while-drilling (LWD) measurements for high-angle and horizontal wells that have been applied recently with success on the Norwegian continental shelf (NCS). The main benefits from the DDR measurements in the license have been to maximize reservoir exposure by active geosteering, optimize well placement above the oil/water contact (OWC), and increase subsurface understanding. More than 50% of all production wells today on the NCS are highly deviated or horizontal. An operator has tested DDR measurements since 2009. This new while-drilling technology, with its increased depth of investigation and ability to interpret multiple boundaries above and below the wellbore, is regarded as a key technology in reaching the ambitious target recovery rate of 70%. Figure 1 presents the bottomhole-assembly (BHA) architecture for the first DDR LWD tool with depth of investigation in excess of 30 m away from the borehole.
The new suite required a complete redesign of printed circuit board (PCB) electronics in order to meet the temperature-qualification criteria of 200 hours at 200 C with a survivability of 210 C for 4 hours. When the joint development of extreme-high-temperature tools began in May 2014, the goal of the collaboration was to eliminate wireline in wells with temperatures over 175 C. Historically, the need for wireline was driven by the requirement to identify hydrocarbons, measure reservoir properties, and book reserves in high-temperature wells; this was accomplished by using a wireline string consisting of gamma ray (GR), resistivity, formation-density, and neutron-porosity sensors. Because of the 175 C temperature limits of the available LWD technology at that time, there was no viable option to log these wells while drilling. This resulted in valuable rig time spent on additional trips to change out bottomhole assemblies (BHAs), mitigate temperatures, and run wireline to gather this data. This also increased the exposure to nonproductive-time (NPT) events, stuck wireline tools, or loss of data if these tools did not reach bottom.
Dukhan field affords an opportunity to assess alternative near-surface velocity-modeling work flows that specifically integrate microgravity (MGR) and vertical electrical sounding (VES). A pilot study of the Dukhan seismic data demonstrates that integration of MGR/VES into prestack depth migration (PSDM) improves the fidelity of seismic images and results in an improved depth match. The resultant MGR/VES PSDM pilot model improved the velocity model between the surface and top Simsima formation on the basis of visible impact on the deeper structure obtained from imaging and better fit between the seismic depth horizons and well measured depths. The Dukhan field (Figure 1 above) along the southwest coast of Qatar is an elongated anticline that has significant hydrocarbon reservoirs in the Jurassic Arab and deeper formations. In 2007, Qatar Petroleum invested in a new full-field, land and shallow-water 3D-seismic survey of the area.