Production-Logging Technologies Enhance Inflow Profiling in Deepwater Gulf of Mexico
This paper discusses the effectiveness of third-generation (Gen3) production-logging-tool (PLT) technology, which uses co-located digital sensors for simultaneous acquisition of flow data to provide the most accurate characterization of the flow condition at each depth surveyed.
This paper discusses the effectiveness of third-generation (Gen3) production-logging-tool (PLT) technology, which uses co-located digital sensors for simultaneous acquisition of flow data to provide the most accurate characterization of the flow condition at each depth surveyed. The resulting data allow for much-improved processing. The probabilistic interpretive model used in the processing has been updated to incorporate this and future developments in PLT architecture.
The first generation of PLT provided a single, discrete measurement for each sensor along the tool assembly’s length, resulting in long tool assemblies and measurements taken at different points along the flow path. This approach had several drawbacks: long toolstrings, point sensors that only provided a measurement at a single point in the cross section of the flow, and measurements that were not acquired simultaneously at each depth logged. Second-generation PLTs represented an improvement because sensors were arranged as an array, enabling multiple measurements to be made at a single depth. However, the toolstrings were still long and not all were arranged optimally to capture data in the flow path. The Gen3 PLT is one-tenth the length of the first-generation versions and roughly one-third that of the shortest second-generation tools. Digitalization allows for direct measurement of flow conditions and rapid interpretation of results. In multiphase flow and deviated wells, co-locating sensors in a spatial geometry provides the optimal information with which to create a fully accurate picture of the downhole flow.
Description of Gen3 PLT
The PLT described in the paper exemplifies how miniaturization and digitalization are enabling transformational improvements over traditional systems in terms of efficiency and capability. The tool encompasses, within a 3-ft length, up to 24 sensors that collect multiple measurements of fluid properties and fluid movements in a wellbore. These include oil, gas, and water holdup and bubble count, fluid conductivity, phase velocities, pressure, temperature, inclination, rotation, and depth correlation, plus power and communication. The fluid characteristics are locally screened by an array of 8 to 16 tube-shaped probe sensors that are interchangeable, depending on the targeted measurements (Fig. 1).
The tool relies on a refractive index needle-shaped probe with a triphasic sensor to identify and quantify the oil, gas, and water holdups and bubble counts at each point of the array. The geometric design of the sensitive tip, along with the optoelectronics of the sensor, are optimized to discriminate oil, water, and gas with high confidence, overcoming the fact that the refractive indexes of oil and water are close to each other.
The sensor electronics perform rapid computations on the measured refractive index, and integrate intelligent, fast processing for embedded computation of the holdups, enabling the output of the holdups on the basis of the time spent in each phase at each measurement period. The rapid computations also generate the bubble count from the number of phase transitions occurring during the measurement period.
Fluid-identification sensors use the refractive index, resistivity, capacitance, and conductivity of fluids to differentiate them, reducing or eliminating potential sources of error from previous PLT technologies.
To optimize flow characterization in varying flow conditions, the distance of the sensor tips from the pipe wall can be adjusted. This allows for making measurements, either at the periphery of the well section when close to the wall (e.g., in a horizontal well), or to cover a larger area extending from the periphery to the longitudinal axis of the well (e.g., in vertical or inclined wells). The diversity of conditions is related to the inclination of the well or type of multiphase fluid mixture.
The tool can rotate as a result of friction between the centralizer arms and the tubing/casing wall, torque release from the wireline, or a forced rotation induced by a tool accessory. A microelectromechanical systems (MEMS) pressure sensor provides more-stable and -accurate pressure measurements, even in changing well conditions, according to the authors.
Also, according to the authors, the tool is the first downhole measuring device to integrate a functional Doppler flowmeter to measure flow velocity with no moving parts. This poses an interesting alternative to spinners, especially in flows that carry paraffin, scale, asphaltene, sand, debris, or heavy oil. The tube-shaped Doppler probe allows measurement close to the pipe wall for early entries detection. The tool-body Doppler array provides full-bore imaging all around the tool. However, the depth of investigation depends on the ultrasonic-beam dispersion and attenuation, which in some cases limits the flow-profile determination.
The complete paper presents a discussion of the data-processing methodology, which is based on a probabilistic, rather than deterministic, approach. The paper also presents three deepwater Gulf of Mexico case studies, including the PLT probe configuration, processing, and results for each. One well was logged in surface readout mode. The data from the other two wells were recorded in the downhole tool’s memory for retrieval at surface at the end of operations. This flexibility in logging modes optimized operations by addressing the needs of the operation teams.
The authors describe planning, execution, and analysis of data for the wells in detail. In each case, a clear path forward is provided for optimal management of the reservoirs through effective production management.
In the first well, the PLT was run to establish a baseline zonal contribution estimate from the perforated interval of an oil producer that had been choked back to curb sand production (Fig. 2).
The second well targeted two separate reservoirs as a dual-zone commingled producer. The PLT was run to assess remediation options and more accurately allocate reservoir production following a threefold reduction in productivity index and 30% decrease in oil production over a 1.5-year period. A key concern was the potential for a large pressure differential between the upper and lower zones. The increased impairment of the lower zone was verified, and the pressure data extracted from the PLT were used in the intervention design.
The third well had been identified as a suitable water shutoff candidate, with the water thought to be producing uniformly from all zones. The PLT was run to determine if the well would be a candidate for mechanical or chemical shutoff.
- The Gen3 PLT discussed in this paper has been run successfully in multiple deepwater wells and provides the most robust data to date.
- The data are complemented by redundancy of sensors, so if one or several fail, others of the same type are still available.
- When logging with slickline, tool rotation has been difficult to achieve, and further innovation is necessary to assure full characterization of downhole flow.
- A unique advantage of the rotating sensors is that the response of the same sensor can be identified for the entire logged interval along with its position.
- Although digitalization enables creation of very accurate sensors, there is still no better precision in measurements than those made by the same probe across all layers of the producing fluids.
- Doppler data are still being evaluated to either complement or replace traditional velocity profiling with mini-spinners.
This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 196188, “Third-Generation Production-Logging Technologies Enhance Inflow Profiling in Deepwater Gulf of Mexico Reservoirs,” by Glenn Donovan, SPE, Sagar Kamath, and Elizabeth Tanis, SPE, Shell, et al., prepared for the 2019 SPE Annual Technology Conference and Exhibition, Calgary, 30 September–2 October. The paper has not been peer reviewed.