Off-gas 10% of total Carbon AHTL Oil 72% of total Carbon (77% algal carbon recovery) Natural Gas 3.5% of total Carbon in Water & Solids Recycle to Ponds 8% of total Carbon as dissolved CO2 (9% of algal carbon) Reformer & Heater Exhaust 23% of total Carbon (Includes 21% of algal carbon) Natural Gas Drier & Exhaust 3.5% of total Carbon in

We apply Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) for direct characterization of iron-porphyrins in hydrothermal liquefaction (HTL) biocrude oils derived from two algae: Tetraselmis sp. and cyanobacteria. The iron porphyrin compounds are shown to cause catalyst bed plugging during hydroprocessing due to iron deposition. Inductively-coupled plasma optical emission spectrometry (ICP-OES) was utilized for iron quantitation in the plugged catalyst beds formed through hydroprocessing of the two HTL biocrudes and identifies an enrichment of iron in the upper five centimeters of the catalyst bed for Tetraselmis sp. (Fe=100,728 ppm) and cyanobacteria (Fe=115,450 ppm). Direct infusion FT-ICR MS analysis of the two HTL biocrudes with optimized instrument conditions facilitates rapid screening and identification of iron porphyrins without prior chromatographic separation. With FT-ICR MS we identify 138 unique iron porphyrin compounds in the two HTL biocrudes that have similar carbon number and double bond equivalent distributions to the metal porphyrins (e.g. Ni and V) reported for petroleum. No iron porphyrins are observed in the cyanobacteria HTL biocrude after hydroprocessing, which indicates that iron porphyrin structures in the HTL biocrude are degraded during hydrotreatment. Hydrodemetallization reactions that occur through hydroprocessing of HTL biocrudes could be responsible for the decomposition of iron porphyrin structures leading to metal deposition in the catalyst bed that result in catalyst deactivation and bed plugging, and must be addressed for effective upgrading of algal HTL biocrudes.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper is a comprehensive presentation of ALL the methods available for analyzing production data, highlighting the strengths and limitations of each method. These methods include those developed by Arps, Fetkovich, Blasingame and Agarwal-Gardner, as well as a new method called the Flowing Material Balance. Some methods yield recoverable reserves, while others give hydrocarbons-in-place.Traditional (Arps) decline analysis (exponential or hyperbolic) gives reasonable answers in many situations, but has its failings, the most important one being that it completely ignores the flowing pressure data. As a result, it can underestimate or overestimate the reserves.The increase in electronic data measurements has made the flowing pressure as readily available as the flow rate. This enables the use of the more sophisticated methods of analysis, which take into account both the flowing pressure and the production rate.The sequential and systematic use of all these methods gives a consistent and more reliable answer. The strengths and limitations of each method are reviewed, from the simplest exponential decline to the Flowing Material Balance. Two examples are given, one that overestimates reserves, and one that underestimates them.An additional example illustrates the importance of knowing the dominant flow regime.

Long-term shale gas well performance characteristics are generally not well understood. The ultra-low permeability of shale ensures the continuing presence of pressure transient effects during well production. This makes production forecasting a difficult and non-unique exercise. Conventional methods have proven to be too pessimistic, in many cases, because they assume a depletion-dominated system. Recently, more suitable forecasting methods have been developed that account for long-term transient effects. These methods incorporate a transient model (usually linear flow) which transitions into a conventional boundary-dominated flow model after a prescribed time or upon achieving a certain region of investigation. The underlying concept assumes that once a transition to boundary-dominated flow is observed, depletion will dominate the production going forward. Although this methodology has been successfully applied for a variety of tight gas reservoirs, it may not be the right model for fractured shale gas (and some conventional tight gas) reservoirs. Fractured shale gas reservoirs get their productivity from the stimulated reservoir volume (SRV), which may be quite limited in areal extent but is surrounded by a low-permeability reservoir (matrix). Thus, the mechanism for long-term production includes a late-time transition from depletion of the SRV, back to infinite acting (linear or pseudo-radial) flow. This "return" to infinite acting flow may or may not provide contribution to recoverable reserves within a practical time-frame, but it should be considered nonetheless. In this paper we present a straight forward methodology for determining the major well performance characteristics of fractured horizontal shale gas wells, considering the impact of uncertainty and non-uniqueness. The focus will be on determining the dominant flow regimes and bulk properties from the data, and then defining a suitable, simple reservoir model for production forecasting, using practical experience and all available information. Field examples from the Barnett, Marcellus, and Haynesville shales are included.

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