Evaluating a geological formation

Abstract: A geological formation is evaluated by taking core samples of predominantly one type of rock; determining a T2 distribution of a formation lithology and a T2 cuttoff time for each sample; and calculating the formation lithology surrounding the borehole and estimating a variable T2 cuttoff time based on the formation lithology.

Description: This invention relates to a method of evaluating a geological formation, and in particular to a method of evaluating a geological formation using T2 cutoff time. The inexpensive and continued production of hydrocarbons is essential to the maintenance of modern society. In view of a limited world hydrocarbon supply, keeping energy costs low requires a continual improvement in geological formation evaluation and hydrocarbon recovery. This constant quest for improvement requires breakthroughs in well logging technology. Improved formation data logs allow more accurate predictions of where producible hydrocarbon may be found and increase the yield at these sites. Past improvements in the field of hydrocarbon well logging include induction and resistivity tools, acoustic tools, and nuclear tools. The determination of whether a particular geological formation contains producible hydrocarbon can be extraordinarily complicated. Initially, it must be determined what, if anything, a sub-surface formation contains. If it contains fluid, it must be determined whether this fluid is water, hydrocarbon, or both. One difficulty encountered by the hydrocarbon industry is its need to retrieve a hydrocarbon stream from the ground that contains only a limited supply of water or brine. Thus, although an area may contain adequate hydrocarbons, excessive water may make it unsuitable for production. Resistivity tools have been useful in determining whether water is present in an hydrocarbon-rich formation. However, the mere presence of sub-surface water does not give a full picture of whether there exists producible hydrocarbon. This also depends upon the character of the detected water. Thus, resistivity tools are not ideal because they indicate merely the presence of water, and cannot indicate its mobility. When underground water comes up-hole with the retrievable hydrocarbons it is known as being free, movable, or reducible. Conversely, when the underground water remains down-hole at the time of production it is known as being bound, immovable, or irreducible. Thus, if one cannot determine the mobility of the underground water, many potentially productive hydrocarbon zones with high irreducible water saturation are bypassed because of fear of excessive water production. One technology that has proved to be helpful in modern formation evaluation is nuclear magnetic resonance (NMR) technology. This technology assists in the control of water production and identification of pay zones with high irreducible (or bound) water saturation. One such NMR tool is the MRIL® C-type tool which is illustrated in Figure 1 of the accompanying drawings. The MRIL® apparatus is a centralized device containing a permanent magnet and a radio frequency (RF) pulse generator (not shown). The tool as shown has an outer diameter 10 of 6 inches (15.2cm) and a length of about 50 feet (15.2m). A slim version of the tool (not shown) has an outer diameter of 4½ inches (11.4 cm). In an 8 inch (20.3 cm) borehole 150, MRIL® depth of investigation 120 is 4 inches (10.2 cm). The tool's permanent magnet generates a magnetic field of 2500 gauss (5,000 times the strength of the earth's magnetic field) with a field gradient of 17 gauss/centimeter. When random hydrogen nuclei interact with the applied magnetic fields, measurable signals are produced. The primary field of the permanent magnet aligns the hydrogen nuclei in one direction. The tool then uses its radio frequency generator to pulse a second magnetic field perpendicular to the permanent magnet's primary field. This RF generator operates at the Larmor frequency to rotate the nuclei 90° with respect to the alignment induced by the permanent magnet. After the RF pulse is turned off, the nuclei gradually dephase or disorder, causing the signal to decay. MRIL® operates on three close frequencies, which improves the signal to noise ratio and increases the logging speed. The time consumed by the nuclei to completely dephase is called the T2 time, and the time required for the nuclei to return to their initial aligned position is called the T1 time. The T2 time is shorter than the T1 time and has been chosen as the time measured by the current MRIL® C-type tool. This T2 time varies from one hydrogen nucleus to another, depending on the location of the hydrogen in the formation. When the hydrogen is located adjacent an underground rock surface, it comprises immovable or bound water. Surface tension holds this water to the rock surface and causes the water to remain downhole. When this bound fluid is affected by the magnetic field of an NMR tool, the rock causes the bound water to have a shorter T2 time. Movable water, in contrast, lives in the bulk, and not at the surface of a rock. Thus, the T2 time of its hydrogen is unaffected by a rock's surface and so is longer in duration. In this way, movable water may be differentiated from immovable water based on their respective T2 times. Figure 2 of the accompanying drawings is a graph illustrating T2 data. T2 data have two important aspects, known as the T2 distribution 200 and the T2 cut-off 210. The T2 cut-off 210 separates the effective porosity into irreducible porosity 220 and movable porosity 230. In other words, the T2 cut-off is the dividing line between the bound and the free sub-surface water. In contrast, the T2 distribution is used to calculate a distribution of porosity components as a function of their T2 times. Thus, in the T2 distribution, the sum of all porosities whose T2 time is less than the T2 cut-off yields the NMR-bulk volume of irreducible water (MBVI). Similarly, the sum of all porosities whose T2 time is greater than the T2 cut-off furnishes the NMR-determined free fluid index (MFFI). The NMR determined effective formation porosity (MPHI) is then found by adding MBVI and MFFI. The T2 cut-off may not, however, be derived from the T2 distribution. Thus, while the T2 distribution at a particular depth may be derived by the readings of an NMR tool, the determination of the T2 cutoff for a core sample at this time requires laboratory analysis. Besides porosities, NMR measurements also provide better estimates of formation permeabilities than can be derived from conventional logs. Nonetheless, prior art NMR measurement techniques suffer from significant shortcomings. For instance, the T2 cut-off time may vary significantly along the length of a well bore. The prior art ignored such variation and arrived at a single T2 cut-off point by averaging the T2 cut-off times from a number of core samples taken from the borewall. Those in the industry would prefer a more accurate method for determining the T2 cut-off times. A more accurate method would allow refinement of geological formation evaluation so that areas containing significant irreducible water could be produced whereas nearby areas containing significant movable water could be avoided. Ideally, such a method would cost a minimal amount. For example, the method would minimize the number of core samples that should be taken and consolidate into one period the time required for expensive production. We have now devised an improved method of geological formation evaluation, which method overcomes or mitigates some of the shortcomings of the prior art. In one aspect, the present invention provides a method of geological formation evaluation, as defined in claim 1 and a correspondingly adapted device as defined in claim 8. In a preferred procedure according to the invention, an NMR tool is used in the borehole, and either a linear or nonlinear approach is utilised to determining the variable T2 cut-off times. The device of the present invention that determines variable T2 cut-off times, includes means for combining data from a nuclear magnetic resonance tool with other data logs to yield a composite lithology log and means for deriving variable T2 cut-off times based on the composite lithology logs and known T2 cut-off values, either from core or from previous knowledge. Depending upon the characteristics of the formation being analysed, such a device may use either a linear or a nonlinear correlation to derive the estimated variable T2 cut-off values. Thus, the present invention comprises a combination of features and advantages which enable it to overcome or reduce various problems of prior devices. The various characteristics described above, as well as other features, will be readily apparent to those skilled in the art upon reading the following detailed description of the preferred embodiments of the invention, and by referring to the accompanying drawings. In order that the invention may be more full understood, reference is made to further drawings in which: Figure 3 is an illustration of a borehole drilled in accordance with the present invention; and Figure 4 is a flow chart illustration of a preferred series of steps for deriving estimated variable T2 cut-offs. Referring to Figure 3, there is shown a simplified view of a borehole 310, cut through a complex lithology 300. Complex lithology 300 may be heterogeneous and composed of multiple types of rock. For example, borehole 310 may cut through a first depth 320 corresponding primarily to limestone, a second depth 330 corresponding primarily to dolomite, and a third depth 340 corresponding primarily to sandstone. Figure 3 also shows three core sample locations 325, 335, and 345. If the oil company has prior knowledge of the T2 cut-off of such single lithology, there is no need to cut core samples. If not, core samples are recommended for better overall T2 cut-off estimation. Upon the drilling of borehole 310, an operator at the surface 315 typically records a mud log (not shown). As is known in the art, a mud log is a record of information derived from an examination of drilling fluid and cuttings from the formation. As such, the rock composition at any particular depth already is typically made of record. Where rock lithologies are complex, the vertical composition of the cuttings may change up to every half foot. The composition of the subsurface rock at a particular depth as recorded by the mud log may safely be assumed to extend a short distance beyond the borehole wall. Thus, the present invention combines information about lithology, T2 cut-off data, and T2 distribution data to derive a more precise prediction about hydrocarbon producibility at a particular depth. As such, the present invention may indicate the presence of producible hydrocarbon in areas that were previously thought to be barren. Further, this improved accuracy is based on data gathering and procedures that to a great extent were already required in the prior art. Figure 4 illustrates a method according to the present invention to increase the precision with which the hydrocarbon industry may predict whether a formation contains producible hydrocarbon. Initially, a borehole is drilled at step 400. A mud log is normally recorded when a borehole is drilled. This mud log may be used to determine the composition of the subsurface lithology. Correspondingly, there is a general indication of the rock type formation at a particular depth. At step 410, a single core sample is taken for each rock type that may be present in the subsurface formation. Each core sample should be of a pure rock type, or as nearly pure as possible (a minimum of about 80% purity is desired). Thus, as shown in Figure 3, a first core sample 325 corresponding to a first rock type should be taken at a first depth 320, a second core sample 335 corresponding to a second rock type should be taken at a second depth 330, and a third core sample 345 corresponding to a third rock type should be taken at a third depth 340. Since the determination of T2 cut-off times normally requires laboratory analysis, each core sample should then be submitted to a laboratory for determination of its T2 cut-off time at step 420. This laboratory analysis can also include a collection of the point count data to indicate the exact lithology of each core sample. T2 distributions and MPHI should also be collected at step 420. This normally requires insertion of an NMR tool into the borehole 310, such as the MRIL® tool shown in Figure 1. As already explained, MPHI may be obtained from the T2 distribution. The T2 distribution is found from a train of echoes that are produced upon the decay of the hydrogen nuclei. A complex analysis of the echo train is performed by expressing the n th echo (E n ) as an exponential series: where i = 1, 2,..., 8 and where T 2i =2 i+1 milliseconds are T2 times. Solving the T2 system of equations yields a distribution of the porosities associated with the chosen T2 times. Upon determination of MBVI, MFFI, and MPHI, formation permeability (K) may be derived from Coate's equation: K= MPHI C 4 MFFI MBVI 2 where C is a term that reflects the correlation between the pore throat and the pore size of the rock. Alternatively, other expressions for formation permeability may be used. This also is an opportune time for collection of data from other borehole logging tools, such as induction and resistivity tools, acoustic tools, and nuclear tools. Using MPHI and the other available open-hole and cased-hole log response function models, the formation lithology may be calculated at step 430. The use of MPHI as an additional variable when deriving formation lithology improves the accuracy of the resulting logs. The derivation of formation lithology at discrete depths in the formation is done by forming a system of equations, comparing the actual logs with the theoretical logs, and applying well known error minimization techniques. To evaluate the precision of the fit between the original logs and the reconstructed logs, the chi-square of the difference between logs is calculated. In this methodology, weighting factors can be applied to the log data, and geological and petrophysical constraints can be imposed. This approach increases the importance of MPHI and derives the final solution accordingly. The algorithm used is based on the simultaneous optimization of a model f(X,P) within a zone at a depth level s. The incoherence function to be optimized is defined as: where MPHI is in the input log values (Y s,i ) and Y s,i = value of well log i at level s f i = tool response function for well log i X s = vector of variables (porosity, etc.) P = set of initially assumed parameters to be optimized σ s,i = error on well log i M = number of logs plus constraints N = number of depth levels in the zone Step 440 requires the estimation of variable T2 cut-offs. Although the activities specified at step 420 have calculated the T2 distributions for the entire length of the borehole, and the T2 cut-off points have been established for each of the core samples, before step 440 the T2 cut-off times have not been established for any depth between a given two core samples. To resolve this and derive an accurate prediction regarding the depth and location of producible hydrocarbon, variable T2 cut-off times must be derived. One manner of estimating the T2 cut-off time at a particular depth is according to a linear arithmetic average that includes the T2 cutoff times for each lithology and the corresponding lithology volume. The correlation takes the form: where T2 cutoff = T2 cutoff of formation L = total number of lithologies (rock types) V i = fractional volume of lithology I (calculated at step 430) T2 i cutoff = T2 cutoff of lithology i For example, if a formation is made of a mixture of limestone, sandstone, and dolomite, then at any depth the T2 cutoff can be calculated as: T 2 cutoff = V lime T 2 cutoff lime + V dolo T 2 cutoff dolo + V sand T 2 cutoff sand Since the present method core samples are pure or nearly pure rock types, the T2 cut-off for pure rock types has already been found at step 420. In some cases, linear correlation is not adequate in describing the overall T2 cut-off. In such cases, more samples are required, and a more suitable correlation must be derived. It is presently believed that the linear correlation may not be as precise as otherwise when analysing a calcerous sand deposition. Under those conditions a non-linear relationship for derived T2 cutoff times is more appropriate. When predicting the T2 cutoff times for calcerous sand formations, the T2 cutoff times for all the core samples must still be measured. However, it is also necessary to obtain thin-section data on all of the core samples for lithology and mineralogy determination. Under these circumstances, it is believed that the total T2 cutoff time is generally related to the T2 cutoff times of the locations surrounding lithology by the following harmonic average equation: 1 T 2 = 1 T 2 1 + 1 T 2 2 For example, in a lithology of the above-described type containing limestone, sandstone, and dolomite, the equation used to derive this harmonic variable T2 cutoff is believed to be: 1 T 2 = ∝ V lime T 2 lime + βV sand T 2 sand + γV dolo T 2 dolo where ∝,β, and γ depend on rock relaxivity. While preferred embodiments of this invention have been shown and described, modifications thereof can be made by one skilled in the art without departing from the scope of the claims. The embodiments described herein are exemplary only and are not limiting. Many variations and modifications of the system and apparatus are possible and are within the scope of the claims. For example, the above teachings could be adapted for use in a dedicated or general purpose computer or microprocessor.

Claims: A method of geological formation evaluation, which method comprises taking core samples (325;335;345) from a borehole (310), each of said core samples (325;335;345) being predominantly one type of rock; determining a T2 distribution of a formation lithology surrounding said borehole (310) and determining a T2 cut-off time for each of said core samples (325;335;345); combining data from a NMR tool with other data loss to calculate the formation lithology surrounding said borehole; and estimating a variable T2 cut-off time based on said formation lithology. A method according to claim 1, wherein a nuclear magnetic resonance tool (100) is used in determining the T2 distribution. A method according to claim 2, further comprising using the NMR determined effective porosity (MPHI) in calculating the formation lithology. A method according to claim 1, 2 or 3, wherein said variable T2 cuttoff time is estimated by using a linear or non-linear correlation to the T2 cuttoff of each of said core samples (325;335;345). A method according to claim 4, wherein said linear correlation further includes the lithology volume. A method according to any of claims 1 to 5, which includes recording a mud log, and wherein said core samples (325;335;345) are taken from said boreholes (310) based at least on said mud log. A method according to any preceding claim, wherein the predominant rock type in each of said core samples (325;335;345) has a concentration of greater than about 80%. A device (310) for determining variable T2 cuttoff times in geological formation evaluation, which device comprises means for combining data from a nuclear magnetic resonance tool with other data logs to yield a composite lithology log; and means for deriving variable T2 cuttoff times based on said composite lithology log and known T2 cuttoff values, wherein said known T2 cuttoff values are based on wellbore core samples. A device according to claim 8 adapted for use with wellbore core samples of at least 80% purity. A device according to claim 8 or 9 adapted for use with wellbore core samples of predominantly one type of rock. A device according to claim 8, 9 or 10, wherein said deriving means uses a linear or non-linear correlation based on lithology volume. A device according to claim 8, 9, 10 or 11, wherein said combing data means and said deriving means are a computer.

Inventors: ORABY MOUSTAFA, ORABY, MOUSTAFA, Oraby, Moustafa Halliburton, Dubai 1101-1104
Applicants: HALLIBURTON ENERGY SERV INC, HALLIBURTON ENERGY SERVICES, INC.
Application year: 1998
Main classification: G01N33
IPC codes: G01N33, G01R33