Integration of NMR With Other Openhole Logs for Improved Formation Evaluation

2000 ◽  
Vol 3 (06) ◽  
pp. 509-516 ◽  
Author(s):  
Chanh Cao Minh ◽  
Robert Freedman ◽  
Steve Crary ◽  
Darrel Cannon

Summary The recently introduced measurement of total porosity from nuclear magnetic resonance (NMR) tools can help to identify the hydrocarbon type and to improve the determination of formation total porosity (?t) and water saturation (Swt) in combination with other openhole logs. In shaly formations, porosities are difficult to estimate in the presence of hydrocarbons, especially those for gas and light oils. Water saturations are even more difficult to estimate because critical parameters such as clay cation exchange capacities/unit pore volume (QV), the formation factor (F) and formation water resistivity (Rw) might not be known. The latter quantities are essential inputs into the Waxman-Smits and dual-water model saturation equations. In the typical case of shaly gas-bearing formations, both the total porosity corrected for the gas effect and the gas saturation (Sxgas) in the flushed zone can be derived by combining total NMR porosity (?NMR) and density porosity (?density) Adding resistivity logs such as Rxo) and Rt helps to differentiate between gas and oil. Furthermore, the flushed zone water saturation (Sxot) computed from 1?Sxgas can be used in many ways. One procedure uses Sxot in conjunction with the Rxo saturation equation to determine QV or F. Another technique uses Sxot in conjunction with the saturation point (SP) to estimate QV when Rw is known. Yet, another method estimates QV directly from the NMR short relaxation time part of the T2 distribution and use Sxot in conjunction with SP to estimate Rw. The new interpretation procedure follows the sequential shaly sands approach: first, determine porosity, second, determine shaliness, and, third, determine saturation. The new procedure improves on the classical method by offering new ways to compute QV, F and Rw, The methodology is applied to a number of field examples. Introduction Recently, Freedman et al. have shown how to combine ?NMR and ?density to estimate the gas-corrected total porosity ?t and the flushed zone gas saturation in the density magnetic resonance (DMR) method.1 In this paper we build upon their work and integrate NMR logs with other openhole logs in new ways to improve formation evaluation. For hydrocarbon identification, two simple techniques that combine total NMR porosity, density, shallow and deep resistivity logs are shown in a field example. The techniques are simple enough to give a real-time answer when NMR is logged in combination with the above logs. For water saturation determination, total porosity corrected for the hydrocarbon effect and QV is essential. Classical shale sand log analysis first estimates porosity from the density neutron, then corrects for the hydrocarbon effect using Sxot from an Rxo tool in an iterative loop.2 The DMR method does not require any iteration since the linear forms of the density and NMR response equations provide an exact analytical solution of the flushed zone total porosity and saturation. Sxot can then be used in conjunction with an Rxo tool to compute other petrophysical parameters such as QV or F. On the other hand, quantitative use of the SP log in shale sand log analysis was demonstrated by Smits3 in 1968. Integrating SP with NMR and other openhole logs allows the estimation Rw or QV in a two-step SP inversion procedure.4 Both the above techniques to determine QV are applied to a field example. In a second field example, NMR and SP logs are used to compute varying Rw in a fresh water example using continuous QV estimated directly from the NMR short T2 time distribution. The new interpretation methodology is readily extendable to complex lithology, although a multitools solver approach such as the ELAN™ processing method might be preferred.5 (ELAN is a trademark of Schlumberger.) Quicklook Hydrocarbon Identification Gas identification with the DMR method is unambiguous when the deficit between density porosity and total NMR porosity is large [e.g., 6 pore units (p.u.) or more]. When the deficit is not large (a few p.u.), one is not sure whether light oil is present or some gas remains in the pore space after flushing. Because the DMR results depend on the input (gas or light oil), of hydrocarbon type whereas the shallow resistivity does not (it only sees the water phase), it is possible to determine the hydrocarbon type by simply comparing the DMR results with the Rxo results. Rxo?Rt Method A simple method is to compare the flushed zone water saturation determined by the DMR method with the flushed zone water saturation determined from the Rxo tool. If the two saturations agree (meaning that the DMR gas hypothesis is correct) and the Rt tool indicates hydrocarbon, then the hydrocarbon is gas. If the two saturations disagree (meaning that the DMR gas hypothesis is incorrect) and the Rt tool indicates hydrocarbon, then the hydrocarbon is light oil. In the zones where Swt<0.7 (a given saturation cutoff), hydrocarbon is present, and if Sxot, DMR-gas? Sxot, Rxo, then gas or light oil is present.

2021 ◽  
pp. 4702-4711
Author(s):  
Asmaa Talal Fadel ◽  
Madhat E. Nasser

     Reservoir characterization requires reliable knowledge of certain fundamental properties of the reservoir. These properties can be defined or at least inferred by log measurements, including porosity, resistivity, volume of shale, lithology, water saturation, and permeability of oil or gas. The current research is an estimate of the reservoir characteristics of Mishrif Formation in Amara Oil Field, particularly well AM-1, in south eastern Iraq. Mishrif Formation (Cenomanin-Early Touronin) is considered as the prime reservoir in Amara Oil Field. The Formation is divided into three reservoir units (MA, MB, MC). The unit MB is divided into two secondary units (MB1, MB2) while the unit MC is also divided into two secondary units (MC1, MC2). Using Geoframe software, the available well log images (sonic, density, neutron, gamma ray, spontaneous potential, and resistivity logs) were digitized and updated. Petrophysical properties, such as porosity, saturation of water, saturation of hydrocarbon, etc. were calculated and explained. The total porosity was measured using the density and neutron log, and then corrected to measure the effective porosity by the volume content of clay. Neutron -density cross-plot showed that Mishrif Formation lithology consists predominantly of limestone. The reservoir water resistivity (Rw) values of the Formation were calculated using Pickett-Plot method.   


2016 ◽  
Author(s):  
Ahmed Abouzaid ◽  
Holger Thern ◽  
Mohamed Said ◽  
Mohammad ElSaqqa ◽  
Mohamed Elbastawesy ◽  
...  

ABSTRACT The evaluation of logging data in shaly sand reservoirs can be a challenging task, particularly in the presence of accessory minerals such as glauconite. Accessory minerals affect the measurements of conventional logging tools, thus, introducing large uncertainties for estimated petrophysical properties and reservoir characterization. The application of traditional Gamma Ray and Density-Neutron crossover methods can become unreliable even for the simple objective of differentiating reservoir from non-reservoir zones. This was the situation for many years in the glauconite-rich Upper Bahariya formation, Western Desert, Egypt. Formation evaluation was challenging and the results often questionable. Adding Nuclear Magnetic Resonance (NMR) Logging While Drilling (LWD) data in three wells changed the situation radically. The NMR data unambiguously indicate pay zones and simplify the interpretation for accurate porosity and fluid saturation dramatically. Key to success is NMR total porosity being unaffected by the presence of accessory minerals. NMR moveable fluid directly points to the pay zones in the reservoir, while clay-bound and capillary-bound water volumes reflect variations in rock quality and lithology. Although the NMR total porosity is lithology independent, the presence of glauconite affects the NMR T2 distribution by shifting the water T2 response to shorter T2 times. This requires an adjustment of the T2 cutoff position for separating bound water from movable hydrocarbons. A varying T2 cutoff was computed by comparing NMR bound water to resistivity-based water saturation. The calibrated T2 cutoff exhibits an increase with depth indicating a decreasing amount of glauconite with depth throughout the Upper Bahariya formation. Based on these volumetrics, an improved NMR permeability log was calculated, now accurately delineating variations in rock quality throughout the different pay zones. In addition, viscosity was estimated from the oil NMR signal. The estimated values match the expected values very well and illustrate the potential of NMR to indicate viscosity variations. Many of these results are available today already in real-time by transmitting NMR T2 distributions to surface while drilling. Besides the application for formation evaluation, the data can be used to initiate optimized side-tracking and completion decisions directly after finishing the drilling operations.


2020 ◽  
Vol 5 (2) ◽  
pp. 69-75
Author(s):  
Raja Asim Zeb ◽  
Muhammad Haziq Khan ◽  
Intikhab Alam ◽  
Ahtisham Khalid ◽  
Muhammad Faisal Younas

The lower Indus basin is leading hydrocarbon carriage sedimentary basin in Pakistan. Evaluation of two sorts out wells namely Sawan-2 and Sawan-3 has been assumed in this work for estimation and dispensation of petro physical framework using well log data. The systematic formation assessment by using petro physical studies and neutron density cross plots reveal that lithofacies mainly composed of sandstone. The hydrocarbon capability of the formation zone have been mark through several isometric maps such as water saturation, picket plots, cross plots, log analysis Phie vs depth and composite log analysis. The estimated petro physical properties shows that reservoir have volume of shale 6.1% and 14.0%, total porosity is observed between 14.6% and 18.2%, effective porosity ranges 12.5-16.5%, water saturation exhibits between 14.05% and 31.58%, hydrocarbon saturation ranges 68.42% -86.9%, The lithology of lower goru formation is dominated by very fine to fine and silty sandstone. The study method can be use within the vicinity of central Indus basin and similar basin elsewhere in the globe to quantify petro physical properties of oil and gas wells and comprehend the reservoir potential.


Author(s):  
S. M. Talha Qadri ◽  
Md Aminul Islam ◽  
Mohamed Ragab Shalaby ◽  
Ahmed K. Abd El-Aal

AbstractThe study used the sedimentological and well log-based petrophysical analysis to evaluate the Farewell sandstone, the reservoir formation within the Kupe South Field. The sedimentological analysis was based on the data sets from Kupe South-1 to 5 wells, comprising the grain size, permeability, porosity, the total cement concentrations, and imprints of diagenetic processes on the reservoir formation. Moreover, well log analysis was carried on the four wells namely Kupe South 1, 2, 5 and 7 wells for evaluating the parameters e.g., shale volume, total and effective porosity, water wetness and hydrocarbon saturation, which influence the reservoir quality. The results from the sedimentological analysis demonstrated that the Farewell sandstone is compositionally varying from feldspathic arenite to lithic arenite. The analysis also showed the presence of significant total porosity and permeability fluctuating between 10.2 and 26.2% and 0.43–1376 mD, respectively. The diagenetic processes revealed the presence of authigenic clay and carbonate obstructing the pore spaces along with the occurrence of well-connected secondary and hybrid pores which eventually improved the reservoir quality of the Farewell sandstone. The well log analysis showed the presence of low shale volume between 10.9 and 29%, very good total and effective porosity values ranging from 19 to 32.3% as well as from 17 to 27%, respectively. The water saturation ranged from 22.3 to 44.9% and a significant hydrocarbon saturation fluctuating from 55.1 to 77.7% was also observed. The well log analysis also indicated the existence of nine hydrocarbon-bearing zones. The integrated findings from sedimentological and well log analyses verified the Farewell sandstone as a good reservoir formation.


2021 ◽  
Author(s):  
Chanh Cao Minh ◽  
Vikas Jain ◽  
David Maggs ◽  
Kais Gzara

Abstract We have shown previously that while total porosity is the weighted sum of density and neutron porosities, hydrocarbon volume is the weighted difference of the two. Thus, their ratio yields hydrocarbon, or equivalently, water saturation (Sw). In LWD environments where negligible invasion takes place while drilling, we investigate whether Sw derived from LWD density-neutron logs could approach true Sw in unknown or mixed water salinity environments. In such environments, it is well known that Sw determined from standalone resistivity or capture sigma logs is uncertain due to large water resistivity (Rw) or capture sigma (Σw) changes with salinity. On the other hand, the water density (ρw) and hydrogen index (HIw) variations with salinity are much less (Table 1). Hence, the water point on the density neutron crossplot does not move with salinity as much as the water point on a sigma-porosity crossplot does. Similarly, the water point on a resistivity-porosity Pickett plot would move drastically with changes in Rw. Also, because the hydrocarbon effect on density-neutron logs is much less in oil than in gas, the weights in the density-neutron porosities can be conveniently set at midpoint in light oil-bearing reservoirs without compromising porosity and saturation results. Thus, a quicklook estimate of Sw from density-neutron logs is the normalized ratio of the difference over the sum of density and neutron porosities. The normalization factor is a function of the hydrocarbon density. We also build a graphical Sw overlay for petrophysical insights. We tested the LWD density-neutron derived Sw in two Middle East carbonate oil wells that have mixed salinity. The two wells were extensively studied in the past. In the first well, the reference Sw is given by the joint-inversion of resistivity-sigma logs, corroborated with Sw estimated from multi-measurements time-lapsed analysis, and validated with water analysis on water samples taken by formation testers. In the second well, comprehensive wireline measurements targeting mixed salinity such as dielectric and 3D NMR were acquired to derive Sw, and complemented by formation tester sampling, core measurements, and LWD resistivity-sigma Sw. In both wells, density-neutron quicklook Sw agrees surprisingly well with Sw from other techniques. It may lack the accuracy and precision and the continuous salinity output but is sufficient to pinpoint both flooded zones and bypassed oil zones. Since density-neutron is part of triple-combo data that are first available in well data acquisition, it is recommended to go beyond porosity application and compute water saturation (Sw) in unknown or mixed salinity environments. The computation is straightforward and can be useful to complement other established techniques for quick evaluation in unknown or mixed water salinity environments.


1999 ◽  
Vol 39 (1) ◽  
pp. 437
Author(s):  
P.J. Boult ◽  
R. Ramamoortby ◽  
P.N. Theologou ◽  
R.D. East ◽  
A.M. Drake ◽  
...  

The failure of conventional log interpretation of low resistivity gas-bearing reservoirs in the Lower Cretaceous Pretty Hill Sandstone, onshore Otway Basin, has led to the use of the saturation versus height, Leverett J function as a basis for predicting hydrocarbon saturation.The recent application of a new method of proprietary core analysis (corEVAL™*) in the 1998 gas discovery well Redman–1, allowed the derivation of a more realistic Leverett J function to water saturation transform for the Pretty Hill Sandstone. Furthermore, this transform could be applied beyond the cored interval to the remaining reservoir section by calibrating the core with its nuclear magnetic resonance response. An algorithm, which converts Schlumberger's combinable magnetic resonance (CMR*) cumulative T2 distributions into a pseudo- capillary pressure curve, has been derived enabling the calculation of gas saturation directly from this log. The CMR derived permeability log also assisted in facies differentiation of the reservoir section and in the selection of wireline pressure and formation fluid sampling points.The combined application of nuclear magnetic resonance technology and proprietary core analysis, independently validated by formation sample and test data, resulted in a 30% increase over previous methods, in average gas saturation in the reservoir being calculated. This has lead to a predicted increase in estimated gas in place at the Redman Field


2001 ◽  
Vol 4 (03) ◽  
pp. 209-220 ◽  
Author(s):  
Chanh Cao Minh ◽  
Greg Gubelin ◽  
Raghu Ramamoorthy ◽  
Stuart McGeoch

Summary For environmental reasons, there are times when the use of radioactive chemical sources for density and neutron logging is not possible. The inability to use these logging tools seriously affects porosity determination in gas-bearing reservoirs. Several tools, such as the nuclear magnetic resonance (NMR) tool, the sonic tool, or a minitron-based tool, determine porosity without using a radioactive source. These tools, however, are influenced by many effects and, when used alone, cannot deliver an accurate gas-independent porosity. A new methodology that combines sonic and NMR logs for improved porosity evaluation in gas-bearing reservoirs is proposed. The first variant of the method uses the sonic compressional transit time and the total NMR porosity (ft, NMR) to determine the total porosity, corrected for the gas effect, and the flushed-zone gas saturation. In this approach, a linear time-averaged equation corrected for compaction is applied to the sonic compressional log. The simplicity of the solution, much like the previously published DMR1 Density-Magnetic Resonance Interpretation Method, allows fast, easy computation and a complete error analysis to assess the quality of the results. In the second variant of the method, we show that the rigorous Gassman equation has a very similar response to the Raymer-Hunt-Gardner (RHG) equation for a water/gas mixture. This allows substitution of the complex Gassman equation by the much simpler RHG equation in the combined sonic-NMR (SMR) technique to estimate total porosity and flushed-zone gas saturation in gas-bearing formations. Both techniques are successfully applied to an offshore gas well in Australia. In this well, the porosity in the well-compacted sands is in the 20 to 25 p.u. range and the compaction factor is approximately 0.77. The sonic-magnetic resonance results compared favorably to the established density-magnetic resonance results and also to core data. In another offshore gas well from the North Sea, the porosity in the highly uncompacted sands is in the 35 to 40 p.u. range, and the compaction factor is around 1.85. Both SMR techniques were able to produce a very good porosity estimate comparable to that estimated from the density-neutron logs. Introduction Many authors have discussed the applications of sonic logs in gas-bearing formations.2–4 Stand-alone sonic techniques that use Wyllie's equation or the RHG equation are based on empirical observations of water-saturated samples that are extended to water/gas mixtures.5,6 Stand-alone sonic techniques that involve the Gassman theory are generally too complex for the petrophysicist to consider the effects of many sonic moduli parameters that must be determined to solve for porosity.7–9 Other authors have discussed the applications of NMR logs in gas-bearing formations.10,11 Porosity logs derived from NMR alone suffer from the low hydrogen index of the gas and the long T1 polarization time of the gas when the data is acquired with insufficient wait time. To provide a robust estimate of total porosity in gas-bearing formations, a combined density-NMR technique has been proposed. However, density logging uses a radioactive chemical source, and in certain sensitive environments, it is not used because the radioactive source might be lost in the hole. The sonic-magnetic resonance technique has been developed to provide an accurate porosity in these situations. This paper will demonstrate the following:The Gassman and RHG methods predict very similar sonic responses.Both Gassman and RHG sonic porosities are quite insensitive to fluid type, and hence to water saturation.The solution of the Gassman approach is more complex, requiring five parameters compared to only one for the RHG method (RHG is, therefore, more practical).Combining ft, NMR and RHG provides a good estimate of porosity in gas-bearing formations.Combining ft, NMR and a modified Wyllie scheme gives a simple analytic solution analogous to the DMR method.Gas-corrected porosity could be estimated at the wellsite by rescaling the sonic log. The ft, NMR/RHG and ft, NMR/Wyllie schemes are applied to two field examples. The results are compared to those from DMR, to core data in the first well, and to density/neutron analysis in the second well. Sonic Porosity Equations The three methods (in order of increasing complexity) used to compute sonic porosity from the compressional slowness are based on the Wyllie, RHG, and Gassman formulas. In this section, each approach is analyzed, and the predictions from each are compared with the others. Wyllie Method. The Wyllie equation is Equation 1 Eq. 1 can be rearranged intoEquation 2a withEquation 2b In these equations, f=porosity, ?tc=the sonic compressional slowness, ?tma=the matrix compressional slowness, ?tf=the fluid compressional slowness, and Cp=the compaction factor needed to correct the sonic porosity to the true porosity.


2017 ◽  
Vol 54 (3) ◽  
pp. 181-201
Author(s):  
Rebecca Johnson ◽  
Mark Longman ◽  
Brian Ruskin

The Three Forks Formation, which is about 230 ft thick along the southern Nesson Anticline (McKenzie County, ND), has four “benches” with distinct petrographic and petrophysical characteristics that impact reservoir quality. These relatively clean benches are separated by slightly more illitic (higher gamma-ray) intervals that range in thickness from 10 to 20 ft. Here we compare pore sizes observed in scanning electron microscope (SEM) images of the benches to the total porosity calculated from binned precession decay times from a suite of 13 nuclear magnetic resonance (NMR) logs in the study area as well as the logarithmic mean of the relaxation decay time (T2 Log Mean) from these NMR logs. The results show that the NMR log is a valid tool for quantifying pore sizes and pore size distributions in the Three Forks Formation and that the T2 Log Mean can be correlated to a range of pore sizes within each bench of the Three Forks Formation. The first (shallowest) bench of the Three Forks is about 35 ft thick and consists of tan to green silty and shaly laminated dolomite mudstones. It has good reservoir characteristics in part because it was affected by organic acids and received the highest oil charge from the overlying lower Bakken black shale source rocks. The 13 NMR logs from the study area show that it has an average of 7.5% total porosity (compared to 8% measured core porosity), and ranges from 5% to 10%. SEM study shows that both intercrystalline pores and secondary moldic pores formed by selective partial dissolution of some grains are present. The intercrystalline pores are typically triangular and occur between euhedral dolomite rhombs that range in size from 10 to 20 microns. The dolomite crystals have distinct iron-rich (ferroan) rims. Many of the intercrystalline pores are partly filled with fibrous authigenic illite, but overall pore size typically ranges from 1 to 5 microns. As expected, the first bench has the highest oil saturations in the Three Forks Formation, averaging 50% with a range from 30% to 70%. The second bench is also about 35 ft thick and consists of silty and shaly dolomite mudstones and rip-up clast breccias with euhedral dolomite crystals that range in size from 10 to 25 microns. Its color is quite variable, ranging from green to tan to red. The reservoir quality of the second bench data set appears to change based on proximity to the Nesson anticline. In the wells off the southeast flank of the Nesson anticline, the water saturation averages 75%, ranging from 64% to 91%. On the crest of the Nesson anticline, the water saturation averages 55%, ranging from 40% to 70%. NMR porosity is consistent across the entire area of interest - averaging 7.3% and ranging from 5% to 9%. Porosity observed from samples collected on the southeast flank of the Nesson Anticline is mainly as intercrystalline pores that have been extensively filled with chlorite clay platelets. In the water saturated southeastern Nesson Anticline, this bench contains few or no secondary pores and the iron-rich rims on the dolomite crystals are less developed than those in the first bench. The chlorite platelets in the intercrystalline pores reduce average pore size to 500 to 800 nanometers. The third bench is about 55 ft thick and is the most calcareous of the Three Forks benches with 20 to 40% calcite and a proportionate reduction in dolomite content near its top. It is also quite silty and shaly with a distinct reddish color. Its dolomite crystals are 20 to 50 microns in size and partly abraded and dissolved. Ferroan dolomite rims are absent. This interval averages 7.1% porosity and ranges from 5% to 9%, but the pores average just 200 nanometers in size and occur mainly as microinterparticle pores between illite flakes in intracrystalline pores in the dolomite crystals. This interval has little or no oil saturation on the southern Nesson Anticline. Unlike other porosity tools, the NMR tool is a lithology independent measurement. The alignment of hydrogen nuclei to the applied magnetic field and the subsequent return to incoherence are described by two decay time constants, longitudinal relaxation time (T1) and transverse relaxation time (T2). T2 is essentially the rate at which hydrogen nuclei lose alignment to the external magnetic field. The logarithmic mean of T2 (T2 Log Mean) has been correlated to pore-size distribution. In this study, we show that the assumption that T2 Log Mean can be used as a proxy for pore-size distribution changes is valid in the Three Forks Formation. While the NMR total porosity from T2 remains relatively consistent in the three benches of the Three Forks, there are significant changes in the T2 Log Mean from bench to bench. There is a positive correlation between changes in T2 Log Mean and average pore size measured on SEM samples. Study of a “type” well, QEP’s Ernie 7-2-11 BHD (Sec. 11, T149N, R95W, McKenzie County), shows that the 1- to 5-micron pores in the first bench have a T2 Log Mean relaxation time of 10.2 msec, whereas the 500- to 800-nanometer pores in the chlorite-filled intercrystalline pores in the second bench have a T2 Log Mean of 4.96 msec. This compares with a T2 Log Mean of 2.86 msec in 3rd bench where pores average just 200 nanometers in size. These data suggest that the NMR log is a useful tool for quantifying average pore size in the various benches of the Three Forks Formation.


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