Trevor Hughes

Determining cement composition by Fourier transform infrared spectroscopy

Abstract A diffuse reflectance mid-infrared Fourier transform spectroscopy (DRIFTS) method is described for obtaining high quality Fourier transform infrared (FTIR) spectra of cements. DRIFT spectra of synthetic C3S, C2S, C3A, and C4AF and of pure gypsum, bassanite, anhydrite, syngenite, and calcite are shown. Typical spectra of American Petroleum Institute class G and class A cements display characteristic features which can be related qualitatively to variations in the constituent minerals. For quantitative analysis, the FTIR spectra of 156 cements of varied origin and known elemental composition have been used to construct multivariate calibration models. These relate the spectrum to composition (expressed in terms of nine mineral components and five minor oxides) and allow the composition of unknown cements to be determined rapidly from the FTIR spectrum alone. Error estimates are given.

Physico-chemical studies on a commercial food-grade xanthan — I. Characterisation by sedimentation velocity, sedimentation equilibrium and viscometry

A popular commercially available xanthan polysaccharide ‘Keltrol RD’ has been characterised by sedimentation velocity (Schlieren optics), sedimentation equilibrium (Rayleigh interference optics), and viscometry with regard to: (i) homogeneity; (ii) molecular weight; (iii) gross conformation; and (iv) critical overlap concentration, c∗. Studies were conducted in phosphate-chloride buffer (pH = 6·5, I = 0·30). Preparations were shown to be homogeneous with a characteristic hypersharp Schlieren peak from sedimentation velocity. Despite the low c∗ value (~0·5mg/ml) it was still possible to obtain meaningful physical measurements in the dilute solution regime with a weight average molecular weight Mw = (5·9 ± 1·1) × 106mg/mol, the second thermodynamic (‘osmotic pressure’) virial coefficient of (3·4 ± 0·3) × 10−4ml mol g−2, a sedimentation coefficient S020, w = (12·97 ±0·26) S, a sedimentation concentration regression parameter ks of (2127 ± 85)ml/g and an intrinsic viscosity [η]= (7534 ± 2717) ml/ g. From these data it is also possible to estimate the two ‘hydration independent’ shape parameters II and the Wales-van Holde ratio ks[η]; the values obtained (~ 0·53 ± 0·20 and ~ 0·28 ± 0·10, respectively) are consistent only with a stiff, elongated molecule of aspect ratio ~70:1.

Anomalous stability of aqueous boehmite dispersions induced by hydrolyzed aluminium poly-cations

Abstract Aqueous dispersions of colloidal boehmite rods turn into strong gels when the concentration of (1–1) electrolyte concentrations becomes exceeds 50 mM. However, after addition of aluminium chlorohydrate (ACH) the rods remain stable up to salt concentrations as high as 2 M. Moreover the boehmite-ACH dispersions with an aspect ratio of 19 quickly separate into an isotropic and a liquid crystal nematic phase above a typical threshold concentration of 2 v/v%. It is known that ACH forms polynuclear cations at mild acidic conditions. The anomalous stability as encountered in these dispersions is explained by assuming that these hydrolyzed poly-cations cause a shift of the charge carrying surface.

Nonfouling capture-release substrates based on polymer brushes for separation of water-dispersed oil droplets.

We have demonstrated capture and release of underwater-oil droplets based on fouling-resistant surfaces coated with pH-responsive polymer brushes. In response to the change of environmental pH, oil droplets were captured on the polymer brush-modified surfaces in the high adhesion state. As the droplet volume increased upon coalescence with other oil droplets in the aqueous phase, the captured droplets eventually self-released from the surfaces under the influence of buoyancy and rose to the air-water interface. The fact that the polymer brush surfaces were partially oil-wettable (high oil-in-water contact angles) enabled the adhesion but not the spreading of oil droplets. This allowed buoyancy release of oil droplets and led to fouling-resistant surfaces that could be reused for capture-release of more oil droplets. The practicality and versatility of this oil droplet capture-release system was demonstrated using monodisperse and polydisperse hydrocarbon oil compositions in purified water, tap water, and brines in which the salt concentration was as high as that of seawater.

Using Artificial Neural Networks to Predict the Quality and Performance of Oil-Field Cements

Inherent batch-to-batch variability, aging, and contamination are major factors contributing to variability in oil-field cement-slurry performance. Of particular concern are problems encountered when a slurry is formulated with one cement sample and used with a batch having different properties. Such variability imposes a heavy burden on performance testing and is often a major factor in operational failure. We describe methods that allow the identification, characterization, and prediction of the variability of oil-field cements. Our approach involves predicting cement compositions, particle-size distributions, and thickening-time curves from the diffuse reflectance infrared Fourier transform spectrum of neat cement powders. Predictions make use of artificial neural networks. Slurry formulation thickening times can be predicted with uncertainties of less than 10 percent. Composition and particle-size distributions can be predicted with uncertainties a little greater than measurement error, but general trends and differences between cements can be determined reliably. Our research shows that many key cement properties are captured within the Fourier transform infrared spectra of cement powders and can be predicted from these spectra using suitable neural network techniques. Several case studies are given to emphasize the use of these techniques, which provide the basis for a valuable quality control tool now finding commercial use in the oil field.