Soraya S. Betancourt

Predicting Downhole Fluid Analysis Logs to Investigate Reservoir Connectivity

This paper was selected for presentation by an IPTC Programme Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the International Petroleum Technology Conference and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the International Petroleum Technology Conference, its officers, or members. Papers presented at IPTC are subject to publication review by Sponsor Society Committees of IPTC. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the International Petroleum Technology Conference is prohibited. Permission to reproduce in print is restricted to an

Analyzing Reservoir Fluid Composition In-Situ in Real Time: Case Study in a Carbonate Reservoir

Near-infrared (NIR) spectroscopy is used to provide in-situ quantitative characterization of reservoir fluids during wireline sampling using five representative composition groupings (C1, C2–C5, C6+, CO2, and water). This information is vital for the proper execution of wireline fluid sampling jobs. Time variances of fluid compositions, along with absolute compositions, give us important clues about the phase and contamination level of the capturing samples in real time. In addition, quantitative compositional analysis during wireline sampling provides immediate identification of the critical fluid issues, thereby enabling optimization of the sample acquisition program. Laboratory pressure-volume-temperature (PVT) analysis requires samples that are captured in single phase and are relatively free from mud filtrate contamination. Such information is essential for reservoir management and flow simulation modeling. This paper consists of three parts. The first part covers laboratory NIR spectroscopic study of petroleum fluids at elevated pressures and temperatures. This extensive database, coupled with principal components regression (PCR) technique, establishes the feasibility of such an in-situ compositional analysis. The second part reports shop test results on a downhole experimental prototype. The tool estimates density for each composition group for more than 10 live fluids at conditions simulating a petroleum reservoir. Typically, the measured mass fraction for each composition group agrees with the mass fraction acquired from PVT analysis within ±5% accuracy. The final part presents a field test case study conducted in an onshore carbonate reservoir in the United Arab Emirates (UAE). A gas injection pilot has been running for years, and a comprehensive monitoring program is in place. The first field trial of the subject technology in an observation well successfully identified the presence of injected gas, as determined by fluid compositions. This result was later found to be in good agreement with laboratory PVT analysis.

Integration of In-Situ Fluid Measurements for Pressure Gradients Calculations

Reservoir fluids often show complex compositional behaviors in single columns in equilibrium due to combination s of gravity, capillary and chemical forces. Frequently non equilibrium or non stationary state conditions are also encountered, for instance due to thermal forces act ing. Recognizing these behaviors downhole is a complex process that requires a greater number of data points, flui d samples and associated laboratory analysis. Pressure gradients with wireline formation testers are traditionally used to evaluate fluid density, fluid contacts, and layer connectivity in exploration settings. This in formation is today supplemented by downhole fluid analysis (DFA) measurements to reveal possible reservoir fluid heterogeneities.

DFA Connectivity Advisor: A New Workflow to Use Measured and Modeled Fluid Gradients for Analysis of Reservoir Connectivity

In deepwater and other high-cost environments, reservoir compartmentalization has proven to be a vexing, persistent problem that mandates new approaches for reservoir analysis. In particular, methods involving reservoir fluids can often identify compartments; however, it is far more desirable to identify reservoir connectivity. Downhole fluid analysis (DFA) has enabled cost-effective measurement of compositional gradients of reservoir fluids both vertically and laterally. Modeling of dissolved gas-liquid gradients is readily accomplished using a cubic equation of state (EOS). Modeling of dissolved solid (asphaltenes)liquid gradients can be achieved using the newly developed Flory-Huggins-Zuo equation of state (FHZ EOS) with its reliance on the nanocolloidal description of asphaltenes within the Yen-Mullins model. The combination of new technology (DFA) and new science (FHZ EOS) provides a powerful means to address reservoir connectivity. It has previously been established that the process of equilibration of reservoir fluids generally requires good reservoir connectivity. Consequently, measured and modeled fluid equilibration is an excellent indicator of reservoir connectivity. However, some reservoir fluid processes are faster than equilibration rates of reservoir fluids. The often slow rate of fluid equilibration makes it a suitable indicator of connectivity. Consequently, measurement of disequilibrium can still be consistent with reservoir connectivity. Moreover, the two fluid gradients, dissolved gas-liquid versus dissolved solid-liquid can be separately responsive to different fluid processes, thereby complicating understanding. A workflow is developed, the DFA reservoir connectivity advisor, to enable interpretation of the implications of measured fluid gradients specifically with regard to reservoir connectivity. Reservoir connectivity is difficult to establish in any event; analyses of fluid gradients can be placed in a context of the probability of connectivity, thereby significantly improving risk management.

Chain of custody for samples of live crude oil using visible-near-infrared spectroscopy.

In order to design oil production facilities and strategies, it is necessary to acquire crude oil samples from subsurface formations in oil wells in so-called openhole prior to production. In some environments, such as deepwater production of oil, decisions of huge economic importance are based on such samples. To date, there has been little quality control to verify that the crude oils collected in the sample bottles and analyzed up to a year later in the laboratory have any relation to the actual crude oils in the subsurface reservoirs. These high-pressure samples can undergo myriad deleterious alterations. Here, we introduce the chain-of-custody concept to the oilfield. The visible–near-infrared spectrum of the crude oil is measured in situ in the wellbore at the point of sample acquisition. This spectrum is compared with the spectrum measured on putatively the same fluid in the laboratory at the start of laboratory sample analysis. First, quantitative assessment is made of whether the fluid in the (high-pressure) sample bottle remains representative of formation fluids. Second, any specific changes in the spectrum of the fluid can be related to possible process control failures. Here, the entire process of chain of custody is proven. The chain of custody process can rapidly become routine in the petroleum industry, thereby significantly improving the reliability of any process that depends on fluid property determination.