The “bright spots” predicted by the computer model indicate that the well, in a scenario comparable to that shown in Figure 2, is successfully tracking the top of the reservoir over this interval. The “up-down resistivity” overlay confirms the image. In general the smaller resistivity value is indicative of Rt (true resistivity) in the reservoir and the larger resistivity value is driven by the “horn effect.”

In recent years, advances in well placement have taken place simultaneously along two complementary technological fronts: drilling and LWD. On the drilling side, the positioning of the bit in 3-D space has become more precise thanks to the advent and evolution of rotary steerables. On the LWD side, modern sensors capable of deeper reading and higher resolution combined with advanced forward and inverse modeling have helped better determine the location of the bottomhole assembly with respect to reservoir boundaries and, notably, hydrocarbon contacts.

For best long-term recovery and for maximum production rates through the life of a field, wells need to be drilled within the confines of the reservoir at an ideal distance from given boundaries. Exiting the reservoir places the well bore in non-productive intervals and may create drilling difficulties; staying too far from boundaries due to geological uncertainty is not desirable either as it results in significant unswept pockets of oil. In the first case, the reservoir pressure is maintained through gas injection. The ideal well is horizontal, a few feet above the hydrocarbon-water contact.

In the second, more common scenario, reservoir pressure is maintained through water injection. The ideal well location is as close as possible to the top of the reservoir while not penetrating the cap rock.

Advanced proactive geosteering

Until recently, two families of LWD sensors have been routinely used to geosteer. The first one consists of all wellbore imaging devices: azimuthal density, azimuthal gamma ray, and azimuthal-focused micro resistivity. They accurately measure the relative dip and azimuth of the boundary, but this information becomes available only after the well has exited the reservoir. The second family includes traditional resistivity electromagnetic propagation tools. They anticipate intersecting the approaching boundary, sometimes by hundreds of feet. They cannot, however, identify its azimuth. Interpretation, local knowledge, and best practices by the geosteering engineer help complete the missing information but with some risk of error.

A new azimuthal deep resistivity LWD sensor combines the best of both capabilities. Based on electromagnetic propagation, the new instrument can detect events as far as 18 ft (5.5 m) laterally from a wellbore path. Because of its azimuthal beam pattern, the instrument can also help determine the direction to the approaching event. It also creates a 360° image of the formation several feet into the surrounding rock.

Starting with an advanced non-azimuthal wave propagation array, the azimuthal deep resistivity adds a dimension to all measurements by tilting the receiver antennas and acquiring data from all possible transmitter-to-receiver spacings 32 times per tool revolution. Tilt confers directional sensitivity to the array. In addition, the remote receiver R3, also with a tilted angle but with especially enhanced sensitivity, is able to pick up signals from boundaries as far away as 18+ ft from the well bore.

Validating tool capabilities

The validation of the tool’s capabilities was conducted in recorded mode in a well in the Saudi Arabia Eastern Province. No real-time data was transmitted to the surface; i.e., the run was done in “silent mode.” The object of the exercise was to record the tool response as the well crossed boundaries and examine, after the fact, the recorded logs and evaluate their relevance to geosteering. The first level of information came from deep azimuthal images. These images exhibited the same characteristic patterns as near-wellbore images but were much less well resolved and seemed to emanate from deep within the zone surrounding the well bore. They also appeared to carry the same “horn” phenomena typical of wave propagation measurements. Computer modeling prepared before drilling shows the “smile” pattern when drilling up-structure (Figure 4).

When the geology is simple “layer-cake” beds that are basically horizontal, the images do not offer any more information than a simple “up-down resistivity” overlay whereby only apparent resistivity values from the upper and lower sectors are plotted. The “bright spot” indicative of an approaching roof is clearly shown on three images of different depths of investigation, with the brightest being from the farthest image. For scenarios maintaining an appropriate distance to the bright spot on the farthest image ensures that the well tracks the top of the reservoir without exiting into it.

Geosteering with the geosignal

One key measurement from the azimuthal deep resistivity sensor is the “geosignal” or geosteering signal. It provides early detection of approaching boundaries. By design, the geosignal is highly sensitive to boundaries between materials of different resistivity and has excellent resolution. The geosignal can determine the distance to boundary with great accuracy. In the example, the magnitude of the geosignal is safely above the electronic noise floor of the sensor for a boundary located more than 18 ft away from the well bore.

Summary

The memory data from an azimuthal deep resistivity LWD sensor that was run in a well in Saudi Arabia’s Eastern Province was analyzed to validate its future use of this kind of data for proactive geosteering. The evaluation has validated the three complementary methods described above: “up-down” resistivity, deep resistivity images, and the geosignal. Together, they showed approaching boundaries and their relative azimuth with enough advance warning and enough accuracy to allow proper proactive geosteering.

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