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Using Artificial Neural Networks to Predict the Quality And AI Magazine Volume 17 Number 4 (1996) (© AAAI) Articles Using Artificial Neural Networks to Predict the Quality and Performance of Oil-Field Cements P. V. Coveney, P. Fletcher, and T. L. Hughes ■ Inherent batch-to-batch variability, aging, and powder, is obtained by grinding cement clink- contamination are major factors contributing to er. The cement clinker is manufactured by variability in oil-field cement-slurry performance. firing limestone (providing calcium) and clay Of particular concern are problems encountered (providing silicon, aluminum, and iron). Gyp- when a slurry is formulated with one cement sum (calcium sulfate dihydrate) is then added sample and used with a batch having different properties. Such variability imposes a heavy bur- to moderate the subsequent hydration process. den on performance testing and is often a major After grinding the clinker and gypsum, the ce- factor in operational failure. ment powder consists of multisize, multiphase, We describe methods that allow the identi- irregularly shaped particles ranging in size fication, characterization, and prediction of the from less than a micrometer to slightly more variability of oil-field cements. Our approach in- than 100 micrometers. When this starting ma- volves predicting cement compositions, particle- terial is mixed with water, hydration reactions size distributions, and thickening-time curves occur that ultimately convert the water-ce- from the diffuse reflectance infrared Fourier trans- ment suspension into a rigid porous material, form spectrum of neat cement powders. Predic- which serves as the matrix phase for concrete, tions make use of artificial neural networks. Slurry formulation thickening times can be predicted a cement paste-sand-rock composite. with uncertainties of less than ±10 percent. Com- The various chemical phases within the ce- position and particle-size distributions can be pre- ment powder hydrate at different rates and in- dicted with uncertainties a little greater than mea- teract with one another to form various reac- surement error, but general trends and differences tion products. Some products deposit on the between cements can be determined reliably. remaining unhydrated cement particle sur- Our research shows that many key cement faces, but others form as crystals in the water- properties are captured within the Fourier trans- filled pore space between cement particles. form infrared spectra of cement powders and can Moreover, some of the hydration products be predicted from these spectra using suitable contain nanometer-sized pores, so that the size neural network techniques. Several case studies are given to emphasize the use of these tech- range of interest for these materials is from niques, which provide the basis for a valuable nanometers to hundreds of micrometers, or quality control tool now finding commercial use even centimeters if one includes the rock ag- in the oil field. gregates used in concrete. Because of these complexities, many questions remain unan- swered in the science of cementitious materi- ements are among the most widely used als. As with most materials of industrial impor- and the least well understood of all ma- tance, the key relationships between Cterials. Although cements are often processing and underlying physicochemical viewed as simple “low-tech” materials, they properties must be elucidated to obtain better are, in fact, inherently complex over many control over the material in use. length scales. The starting material, cement The most common application of cement Copyright © 1996, American Association for Artificial Intelligence. All rights reserved. 0738-4602-1996 / $2.00 WINTER 1996 41 Articles is, of course, in building construction, where it has been used since at least Roman times. However, the work described here is con- cerned with another important application of cement—in the oil industry, where about three percent of the world’s annual cement output is deployed. Cement is used to line oil and gas wells after drilling by pumping a cement slurry between the well bore and a steel casing inserted into the well, as shown in figure 1. During placement, the cement displaces all the drilling fluid originally pre- sent from the drilling operation itself. The cement then sets to form a low-permeability annulus, which isolates the productive hy- drocarbon-bearing zones of the well from the rest of the formations, surplus water, and the surface. Cement is used almost exclusively for oil- field cementing despite the fact that its per- formance is variable and not completely un- derstood. Cement variability is observed between cements from different manufactur- ers, different cement batches from the same manufacturer, and samples from the same batch of cement that might have aged differ- ently during storage. Because of all these problems, well cementing has remained un- til now more a black art than a science. Various cement-slurry properties, such as compressive strength development, perme- ability to oil and gas, and flow behavior, need to be specified and controlled, taking Figure 1. Cementing an Oil Well. into account the high temperature and pres- The main objective of such well cementing is to sure conditions prevailing down hole. For provide complete and permanent isolation of the oil-field cement slurries, the thickening time formation behind the steel casing previously placed in the bore hole. The cement must be mixed plays a central role during slurry formula- to meet appropriate design parameters and is then tion because it is a measure of the time with- pumped down hole, displacing all drilling mud in which the cement is pumpable (American from the annulus between casing and formation. Petroleum 1982). Experimentally, it is the Spacers or washes can be used along with top and time taken to reach a specified consistency bottom plugs to separate cement from drilling as measured under defined conditions. mud. Centralizers on the outside of the casing are Longer than required thickening times are a used to keep the annular gap as even as possible. potential waste of drilling time and an in- efficient use of expensive chemical additives. Operational problems as a result of short thickening times are especially dramatic be- cause the cement can set prematurely in the casing or pumping equipment. Such major operating failures (MOFs) can necessitate the complete redrilling of a many-thousands-of- feet well bore and can cost from $1 to $2 million; less severe MOFs in which a limited amount of redrilling is required typically cost around $0.6 million. Therefore, consid- erable, time-consuming experimental effort is devoted to precise control of slurry thick- ening times. 42 AI MAGAZINE Articles Application Description: The FTIR Spectra of Cements In view of the overwhelming complexity of SPECULAR REFLECTANCE cement hydration, a valuable quality control tool would be a model predicting perfor- DIFFUSE REFLECTANCE mance properties of a given cement sample prior to its use. However, the mathematical modeling of cement hydration based on mechanistic understanding is still in its in- fancy (but see Coveney and Humphries [1996]). The approach taken here is to dis- pense with detailed physicochemical charac- terization of the cement particles in favor of methods based on a combination of statistics and AI. With this approach, cement composi- tion and performance properties are correlat- ed with a judiciously chosen measurement that implicitly contains key information on Figure 2. Schematic of the Diffuse Reflectance Process. cement composition, particle-size distribu- tion, and surface chemistry. To give the method any chance of commercial success, radiation penetrates the sample and is reflect- this measurement also has to be relatively in- ed from particle surface to particle surface. At expensive and easy to perform on a routine each reflection, a degree of energy absorption basis. occurs as indicated in figure 2. The measurement chosen was based on the Energy is absorbed because of the vibration use of infrared spectroscopy, a common analyt- and stretching of chemical bonds in the ic technique used in the chemical sciences. It molecules of the powder. The reflected light is well known that every chemical species has reemerges from the sample and is collected its own unique infrared spectrum. Indeed, by a second ellipsoidal mirror. The Fourier chemists most commonly use this technique transform technique is used to convert the in a qualitative mode by matching up spec- emergent radiation into a spectrum of ab- tral features in an unknown compound with sorbance versus frequency. The experimental previously recorded spectral data on known method for collecting FTIR spectra of cement compounds available in lookup tables. An ex- powders has been described elsewhere (Hugh- perienced chemist, working in a specified area es et al. 1995, 1994). The wavelength range of of chemistry, can often identify a chemical by the mid-infrared region of the electromagnet- direct visual inspection of its infrared spec- ic spectrum is approximately 2.5 × 10–3 cm to trum. A more specialized yet equally well-es- 2.5 × 10–4 cm or 4000 to 400 wave numbers, tablished application is quantitative analysis of where wave numbers are reciprocal wave- chemical mixtures, wherein measured spectra length in units of cm–1. of unknown chemical composition are re- gressed against linear combinations of in- Information Contained within frared spectra either of the pure chemical Cement FTIR Spectra components or of mixtures of known chemi- Particle Size: The extent of diffuse reflectance cal composition (Beebe and Kowalski 1987). is inherently related to the particle size of the The particular variant used in this work is sample but in a generally unknown manner. that of the Fourier transform infrared (FTIR) Large coarse particles allow the incident radia- spectrum of dry cement powders, sometimes tion to penetrate deeply into the sample, thus known as diffuse reflectance infrared Fourier increasing absorption. However, large particles transform spectroscopy (DRIFTS). In this tech- show greater specular reflectance that distorts nique, white-light radiation from a Michelson the frequency spectrum.
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