Reservoir characterization

In-Situ Fluid-Composition Analyses Improve Reservoir Management

This study focuses on recent experience in Saudi Arabia with crude-oil compositional analyses during pumpout with a wireline formation tester (WFT).

jpt-2017-08-formevalhero.jpg

This study focuses on recent experience in Saudi Arabia with crude-oil compositional analyses during pumpout with a wireline formation tester (WFT). It summarizes experience with the in-situ measurement of methane, ethane, propane, saturates, aromatics, and gas/oil ratio (GOR) on the basis of multivariate optical computing (MOC) conducted at more than 200 pumpout stations in a total of 37 wells drilled with a variety of inclinations, bit sizes, and drilling fluids in several oil and gas fields.

Introduction

In reservoir-fluid characterization performed in the laboratory conventionally, samples of representative formation fluids are analyzed to determine bulk fluid properties, fluid-phase behavior, and chemical properties. Exploration and evaluation wells are often drilled exclusively for fluid-analysis purposes for which the only way to analyze or capture formation fluids is a downhole pumpout WFT (PWFT). Capturing high-quality reservoir samples is one of the most important objectives in any PWFT job.

The keys to ensure fluid cleanup during pumpout are (1) a set of downhole sensors measuring the pumped fluids and (2) the unambiguous contrast between the drilling-mud filtrate and reservoir ­fluids as measured by at least one of these sensors. Avoiding such fluid ambiguity is a challenge in many situations. Optical sensors respond with high sensitivity to chemical compositions of fluids. Implemented downhole, these tools can provide a powerful means of differentiating between the oil-based-mud (OBM) filtrate and reservoir oils.

The most valuable benefit of these measurements is the prompt availability of in-situ fluid-composition data without the additional steps of acquiring, transporting, and analyzing physical fluid samples in the laboratory. This process requires durable, robust, and accurate optical sensors that operate reliably and consistently in the hostile downhole environment. One recently developed optical-sensor system is based on an optical device known as an integrated computational element (ICE) that performs the mathematical operation of MOC. For each fluid component, an ICE “core” is engineered such that only one particular fluid component or property is accentuated in the detector response and everything else is muted. This detector response is then used to infer the abundance of the fluid component of interest. These optical elements are typically very broadband and may have a response that extends from 400 to 5000 nm. The high bandwidth of these optical elements combined with their intrinsic high signal/noise ratio enables laboratory-grade optical analysis downhole.

Methodology

MOC is essentially a real-time optical computer that uses light instead of the complex circuitry of a conventional electronic processor. Specifically, it performs a dot product of an input light spectrum with a preprogrammed filter vector. With optical elements sophisticated enough to capture the complex filter shapes of reservoir-fluid components, the MOC system can measure concentrations of such components very efficiently. The inherent simplicity and passive nature of the MOC method enable a simple and compact implementation of the ICE core technology in challenging environments such as those encountered downhole.

A schematic of the ICE-core MOC platform with a photograph of the ICE-core carousel is shown in Fig. 1. Broadband light is directed through a flow cell, through an ICE-core sensor, and onto the optical detector, whose output can be used to display real-time proportion information. The sensor is mounted on a revolving carousel that rotates various sensors into the optical beam to measure the specific component associated with that sensor. By rotating the carousel, different formation-fluid components can be investigated. The sensors can be added or changed according to fluid properties of interest. The current configuration in the ICE allows for up to 20 ICE cores; how­ever, currently only six such sensors, which are dedicated to GOR, methane, saturates, and aromatics, have been implemented.

jpt-2017-08-181526f1.jpg
Fig. 1—Schematic of the ICE-core MOC platform with a photograph of the ICE-core carousel (top).

 

The optical-sensor module, called the integrated characterization section (ICS), is deployed as part of a WFT tool. Real-time ICS data, as acquired by the logging unit, are displayed along with basic operational information and the outputs from the density, resistivity, and capacitance sensors. The main purpose of this display is to enable fluid-cleanup monitoring and a quick assessment of the chemical composition of reservoir hydrocarbons.

The compositional results at the final stage of cleanup can be summarized in a tabular format. Plots such as these are useful for checking consistency between different samples for data-quality control and for the purpose of field studies. The composition track can be integrated easily into log displays.

Validation

The first validation step was a comparison of the in-situ measurements with laboratory pressure/volume/temperature results performed on fluid samples.

The second validation step establishes consistency with the fluid-density sensor, which works completely independently of the optical module. In a side-by-side comparison of the optical compositional analysis and the fluid density as observed at 23 pumpout stations in eight different wells in one field, sorted by the density value, there is a very clear decreasing trend of methane and saturates (generally associated with light components) and an increasing trend of aromatics and residuals (generally associated with heavier components) with ­increasing density.

The methane and the GOR were also displayed as a crossplot vs. downhole WFT density and vs. each other from a large area with multiple fields (Fig. 10 of the complete paper). Hydrocarbons in this area sourced similarly, where physical and compositional characteristics are expected to correlate similarly in the entire area. The trends revealed by the crossplots in this multiwell study suggest the consistency of different sensor specimens and the uncertainties of the tool while deployed in a multitude of borehole environments.

Results and Discussion

Collecting the ICS results from 37 wells, fields, and reservoirs was planned in three different phases; each phase had its own goals and data-collection strategy. Phase One was for tool operational integrity and data collection in different environments. Phase Two was for optimal tool configuration within the WFT flowline to alleviate the flow-regime effect on the measurement. Locating the ICS before the pump will subject the fluid to reservoir flowing pressure during cleanup and fluid characterization. This drawdown pressure varies considerably, depending on the fluid nature and rock permeability. If the fluid analyzer is on the outlet side of the pump, the fluid is under a constant flowing pressure (hydrostatic pressure), which is predictable and more consistent. One possible drawback of this configuration is the possibility of fluid segregation inside the pump. Phase Three was for selective reservoir fluids to be used for final tool validation and comparison with laboratory results. Also, in this phase, a real-time answer product was fully developed to provide a simple interpretation and fluid characterization in an integrated plot in real time.

Data from Phase Three were used for validation and in-situ hydrocarbon characterization with the new optical fluid analyzers. The in-situ measurement is consistent with the global American Petroleum Institute (API) correlation. Minor deviations are observed at the heavy-hydrocarbon end because it is challenging to achieve low levels of contamination when sampling heavy oils. The addition of an asphaltene ICE core is expected to increase sensitivity and provide additional information to the characterization of these heavier ends.

The increased availability of compositional data provided by this technology greatly improves understanding of the evolution of hydrocarbon systems. For example, API gravity, as well as the saturates and aromatics ratio, typically increases with depth in a given lithological column, with notable exceptions in the Middle East and Russia where the high-API-gravity members are found above the low-API-gravity members. Early ­hydrocarbon-composition data help well-testing simulations and operations under these circumstances.

Also, compositional variations within a single reservoir column have been observed in a number of fields. The emerging discipline of reservoir-fluid geodynamics provides new scientific understanding and mathematical models to describe these variations and to predict the physical behavior of petroleum fluids better. Readily available and consistent in-situ fluid-composition data crucially help reservoir understanding and underpin the selection, validation, and calibration of these models without the lengthy turnaround time of laboratory measurements.

Conclusions

  • The technology has been field tested extensively. The results appear to be highly consistent among different wells, reservoirs, and fields and are in general agreement with laboratory compositional analyses.
  • For quantitative hydrocarbon-composition analysis, ICE data measurements must be taken on fully cleaned-up reservoir hydrocarbons and at static conditions (i.e., no pumping).
  • The high bandwidth of this optical sensor, particularly in the infrared, creates the potential to measure complex fluid components in situ. Currently, sensors for methane, ethane, saturates, aromatics, and GOR are implemented.
  • Additional capabilities are being developed, including characterization of resins and asphaltenes for full analysis and of olefins for OBM-filtrate detection.
  • It is desirable to develop a robust technical capability that enables quantitative compositional interpretation on partially cleaned-up fluids and during pumpout in the presence of both OBM and water-based-mud systems.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 181526, “New Wireline, In-Situ, Downhole Fluid Compositional Analyses To Enhance Reservoir Characterization and Management,” by Gabor Hursan and S. Mark Ma, Saudi Aramco, and Wael Soleiman, Sami Eyuboglu, Neeraj Sethi, and Nacer Guergueb, Halliburton, prepared for the 2016 SPE Annual Technical Conference and Exhibition, Dubai, 26–28 September. The paper has not been peer reviewed.