Geophysical Log Responses Research Articles

Fluid typing in tight sandstone from wireline logs using classification committee machine

Owing to the low porosity and low permeability of tight sandstone reservoirs, the geophysical log responses to different fluids are unclear, and it is difficult to identify the fluid types of some layers from wireline logs. The committee machine is a recently developed hybrid intelligent algorithm that combines expert networks and makes the final judgment through a decision mechanism. Fluid identification by log interpretation is a classification problem in machine learning; thus, we construct a classification committee machine (CCM). It is composed of a back-propagation neural network, a probabilistic neural network, and a decision tree classifier, and the final result is decided by voting. The processing flow of fluid identification from wireline logs is summarized, and the expert networks are optimized. Fluid typing for a gas reservoir and an oil reservoir in the Ordos Basin is conducted and analyzed in detail, and logs that are sensitive to the fluids in layers are chosen as input for the CCM. The prediction results from the CCM are compared with those of the three expert networks. Case studies from the gas field and oilfield show that the CCM can effectively combine intelligent algorithms through a decision-making mechanism and provide more accurate results.

Characteristics of gas hydrate reservoirs and their effect on petrophysical properties in the Muli area, Qinghai-Tibetan plateau permafrost

Gas hydrates occur in the pores of sandstones with low porosity and high clay mineral content and in the fractures of mudstones in the Muli area. This leads to difficulties in the evaluation of gas hydrates using geophysical logs. Understanding the characteristics of gas hydrate reservoirs and the generation mechanisms for geophysical log responses is the basis for log interpretation. In this study, core experiments including scanning electron microscopy, thin section observation, nuclear magnetic resonance, and porosity and permeability measurements were performed to understand the pore structure of gas hydrate reservoirs. X-ray diffraction, X-ray fluorescence, cation exchange, total organic content, and natural gamma spectrometry measurements were conducted to understand the rock composition and its effect on the petrophysical properties of the reservoirs. Reservoir log responses were analyzed and combined with core experimental data. The results showed that pore-type reservoirs with low porosity (0.6%–10.7%) and low permeability (0.005 mD-0.603 mD) belong to tight sandstones and fracture-type reservoirs contain relatively high TOC (0.133%–8.377%). A high resistivity log value is the most significant feature of gas hydrate-bearing reservoirs. An increase in clay mineral content, which is related to more bound water and a higher cation exchange capacity in sandstones, can remarkably reduce resistivity, which results in poor correlation between the resistivity of water-saturated sandstone and porosity. Fractures in mudstone are important storage spaces for gas hydrates. Calcite veins frequently occur in mudstones in the Muli area. If fractures are filled by calcites, the density, resistivity, and velocity of mudstone increase significantly. The velocity log values between gas hydrate-bearing reservoirs and other formations show no significant difference, which is caused by narrow and complex storage spaces, fracture-filling constituents, and poor velocity measurement results related to borehole collapse. This study is helpful to improve the accuracy of evaluation of gas hydrates in the Muli area.

Organic-rich source rock characterization and evaluation of the Cretaceous Qingshankou Formation: results from geophysical logs of the second scientific drilling borehole in the Songliao Basin, NE China

The second continental scientific drilling (SKII east) borehole in the Songliao Basin has been planned to be the deepest borehole to drill through the Cretaceous continental strata under the framework of the International Continental Scientific Drilling Program (ICDP) up to date. This borehole was designed not only to explore the potential relationships between dinosaur extinction and climate environment during the Cretaceous but also to achieve new breakthroughs in oil and gas exploration. The high hydrocarbon (oil and gas) potential of a source rock is highly dependent on its organic content. We used geophysical log data of Borehole SKII east to evaluate the organic content of organic-rich source rock. In the period of the first member in the Qingshankou Formation (K2qn1) from the study area, high accommodation space and anoxic environment could promote organic matter deposition. Firstly, based on geological information and abundant geophysical log data, the basic geophysical characteristics (including petrophysical, lithological, mineralogical, and sedimentary properties) of the Qingshankou Formation in Borehole SKII east were studied. Secondly, geophysical log response characteristics (including resistivity, porosity, radioactivity, mineral and element) of organic-rich source rocks were analyzed. Thirdly, we tried to obtain suitable methods to predict total organic carbon (TOC) content of the target formation with geophysical log data. The laboratorymeasured TOC values of core samples from Borehole SKI south were used to make calibrations with calculated TOC values from geophysical logs. Results from improved ΔlogR technique and Dual_Vsh method are consistent, and indicate that these two methods are effective in this formation. The calculated TOC values from these two methods are relatively desirable, and show that the organic-rich source rocks with high TOC content occurred in the K2qn1 (1646.00~1669.00 m). The highest TOC content can reach 9.15%. The bed thicknesses of organic-rich source rocks are totally up to 7.88 m. These organic-rich source rocks can be considered as excellent. This study demonstrated that improve ΔlogR technique can be applied to evaluate source rocks in the formations without maturity data, and the new method Dual_Vsh is also valid in the Qingshankou Formation. The organic-rich source rock evaluation results could promote further exploration and development of oil and gas resources in the upper Cretaceous formations, Songliao Basin.

Prediction of Coal Proximate Parameters and Useful Heat Value of Coal from Well Logs of the Bishrampur Coalfield, India, Using Regression and Artificial Neural Network Modeling

The energy of coal is expressed by its useful heat value (UHV), and it is the major key player in coal pricing. The objectives of this paper are to obtain (a) the regression relationship between coal proximate parameters and UHVs, and (b) multilayered feed forward neural network (MLFN) models between geophysical log responses and UHVs. Six wells are used for training the networks, and three wells are used for validating the obtained results in the Bishrampur coalfield. The mean square error (MSE) of MLFN models along with correlation (R2) values at their training, validation, and testing stages are the criteria for selecting the best model for estimation of coal proximate parameters and UHVs using geophysical log responses. The final model is selected based on low MSE (≤0.07) and high R2 values (≥0.80) at training, validation, and testing stages. The predicted UHV obtained from the best MLFN model has excellent correlation (R2 = 0.98) with the laboratory determined UHVs of three major coal seams. The pred...

Estimation of ash, moisture content and detection of coal lithofacies from well logs using regression and artificial neural network modelling

Coal core samples and well log data of five exploratory wells of Korba Coalfield (CF), India have been used for prediction of coal facies. The Indian non-coking coal lithofacies are generally classified by analyzing the variation of the geophysical log parameters or by defining the ranges of various proximate parameters (mainly ash % and moisture %) obtained from coal core samples. The objective is to classify each layer as coal, shaly coal and shale depending upon the content of ash % and moisture % of the corresponding layer in coaly horizon. Hierarchical Cluster Analysis (HCA) is applied to classify the non-coal horizons and bands of identified coal seams of each well under the study area based on geophysical log responses: natural gamma ray (NG), high resolution density (HRD) and single point resistance (SPR). Hierarchical clustering separates the zones in a particular coal seam from five wells using the nature of the curve. These zones/clusters are further identified as coal, shaly coal, shale in three wells using regression and multilayer feed forward neural network. The log responses and coal core analyzed proximate parameters of these isolated bands/zones in two wells are used for establishing linear regression and neural network models. The observation shows very satisfactory fit (R2=0.84) between ash content and HRD and poor R2(<0.41) between moisture content and log responses. The MLFN model is based on study of two wells using NG, HRD and SPR log responses as inputs and coal proximate parameters, namely, ash and moisture content as outputs to classify the coal lithofacies. The bands within a coal seam are classified on the basis of the ash and moisture content while training as well as the validation of the model. These linear and MLFN models are used to determine the ash % and moisture % in the remaining three testing wells. MLFN predicted results are more closely to the laboratory analyzed proximate parameters as compared to the results obtained from regression modelling.

Upper Carboniferous stratigraphy of the West Midlands (UK) revised in the light of borehole geophysical logs and detrital compositional suites

The existing lithostratigraphic nomenclature of the late Carboniferous succession of Staffordshire and Shropshire is reviewed in the light of boreholes drilled since 1950. Four lithostratigrahic units are recognized on the basis of sandstone composition, assemblages of detrital clay minerals and geophysical log response. A regionally developed lithostratigraphic marker formed by a palustrine sequence with a distinctive gamma ray response is identified. Recognition of these features permits the identification of former incorrect correlations, and allows revisions to the lithostratigraphy to be proposed. A revision of the macroflora indicates a late Westphalian D to Cantabrian age for the higher part of the succession. © 1997 John Wiley & Sons, Ltd.

Influences of depositional environment and diagenesis on geophysical log response in the South Carolina Coastal Plain: effects of sedimentary fabric and mineralogy

Interpretations of depositional environments and hydrologic units are made routinely from the study of geophysical well logs. Spontaneous potential (SP) and resistivity logs can be used as indicators of textural parameters. Gamma-ray logs denote lithologic zones based on the presence of radioactive material, particularly in fine-grained sediments. On the South Carolina Coastal Plain, surficial fluvially derived cobbles, sands and clays are characterized by very low radioactivity. Weathered paleosurfaces enriched in hydroxy-interlayered vermiculite (HIV) and associated mica produce higher gamma-ray responses at discrete intervals. The underlying sequence of siliciclastic shelf sands, deposited under conditions of eustatic sea-level rise, has high concentrations of smectite and low gamma-ray signatures. Small-scale variability of gamma radiation reflects temporal changes of sub-environments; higher values are recorded in finer-grained, organic-rich nearshore sediments. Calcareous Ecocene sediments are characterized by highly variable signals on the gamma-ray, SP and resistivity logs. Phospharic material, smectite and disseminated organic matter produced very high gamma-ray values; corresponding low SP readings are a function of low macro- to microscale porosity resulting from the fine grain size and authigenic pore-filling cement. Intervals that resemble massively bedded chalks at the macroscale are characterized by low gamma-ray and resistivity values and high SP readings. High SP values result from microposity preserved in biogenic tests rather than intergranular porosity that would be expected for a permeable sand. These observations indicate the importance of incorporating sedimentologic techniques with well-log data for a comprehensive evaluation of subsurface lithologic units.

Geophysical log responses and their correlation with bed‐to‐bed stress contrasts in Paleozoic rocks, Appalachian Plateau, New York

A 1‐km profile of in situ stress and geophysical log data was acquired in the Wilkins well to study the relationship between rock properties and in situ stress contrasts. The Wilkins well penetrates Devonian clastic rocks on the Appalachian Plateau near the town of South Canisteo, New York. Open hole hydraulic fracture stress measurements were made in stratigraphic sequences where geophysical logs indicated significant bed‐to‐bed variations in elastic and lithologic properties. Analysis of stress magnitudes and interval‐averaged geophysical data shows that principal horizontal stress magnitudes correlate directly with elastic stiffness and inversely with clay content. A similar relation is found for older Paleozoic strata penetrated by a well at Auburn, New York. Correlations between stress magnitude and geophysical properties observed in the Wilkins and Auburn wells provide strong evidence that bed to bed stress variations arise from a uniform ENE‐WSW directed strain acting on beds of different Young's modulus rather than from variations in rock shear strength. Because of their high Young's modulus, sandstones, siltstones, and limestones in the northern Appalachian Basin are likely to be stronger barriers to hydraulic fracture propagation than shales. Porosity logs in the Wilkins well show that the large decrease in horizontal stress found at the base of the Rhine street Formation occurs where shales are less compacted. The correlation with undercompaction is consistent with a paleo‐overpressure drainage mechanism as the cause for the stress decrease.

Log-Derived Evaluation of Shaly Clastic Reservoirs

Summary. Reliable evaluation of hydrocarbon resources in shaly clastic reservoir rocks is an important, although difficult, task. This paper briefly reviews the wide variety of interpretive models that has evolved. The discussion focuses on digital shaly-sand evaluation techniques based on the Waxman-Smits model to provide information on total and effective reservoir porosity and fluid distribution, silt content, volume, type (smectite, illite, and chlorite/kaolinite), and distribution modes (dispersed, laminated. and structural) of the clay minerals present in subsurface formations. Case studies from different geologic environments present field experiences in clastic reservoir rocks that exhibit a wide range of porosity and permeability and various amounts, types, and distribution modes of clay minerals. A log-derived formation damage index is also discussed. Finally, emphasis is placed on improved reservoir evaluation of thinly laminated shale/sand intervals through the integration and enhancement of resistivity data, short-spaced dielectric measurements, and/or analytical data-blocking routines. Introduction Few hydrocarbon-bearing clastic reservoirs are essentially free of clay minerals. The significant effect of these minerals on geophysical log responses is well recognized. Ref. 1 represents the first modern collection and comprehensive review of the vast number of technical papers important to the evaluation of shaly clastic reservoir rocks based on geophysical well logging measurements and associated interpretive concepts. For example, Fig. 1 illustrates the generalized response of the various porosity logs to shaliness and hydrocarbon effects. The basic objective in shaly-sand formation evaluation then is a realistic log-derived description of reservoir quality in terms of petrophysical parameters, type, and volume of hydrocarbon resources in place, and expected production behavior. Such evaluation methods may be simple empirical rules, standard analysis concepts, digital wellsite "quick look" techniques, or advanced digital interpretive models used in single-well or multiwell field studies. Basic Considerations In his classic empirical equation, Archie related formation conductivity, formation-water conductivity, and the formation resistivity factor (a function of porosity and cementation exponent) to the formation-water saturation. Archie's equation applies satisfactorily to clean sands, whereas the presence of clay minerals (amount, type, and distribution modes) has a detrimental effect on water saturation calculations. While more than 30 water saturation models have been proposed for shaly-sand reservoir evaluation, most of the major developments can be classified in one of four categories (see Table 1 ). Worthington recently discussed these categories and the evolution of shaly-sand concepts in reservoir evaluation. Concepts based on clay volume, V, exhibit two constraints: being inexact and requiring reliable log-derived V, estimates. 3 The latter, in itself, is no minor task (see Table 2). The most common clay minerals, their chemical composition, matrix density, hydrogen index (HI), cation exchange capacity (CEC), and distribution of potassium, thorium, and uranium as shown by natural gamma ray spectral information are summarized in Table 3. Because a typical shaly clastic reservoir rock and/or a typical shale formation may contain different clay minerals in various amounts, no single clay parameter can be used universally to characterize a specific type of argillaceous sediment or shaly reservoir rock. With the advent of the Waxman-Smits model, reliable water saturation calculations are provided for reservoirs with drastically different clay contents and over a wide range of formation-water salinities. The emphasis is on log-derived evaluation of CEC per total PV, Qv, from specific single or combined well logging parameters. Such QV, estimates from well logs can be based on the spontaneous potential curve, gamma ray, natural gamma ray spectral data (potassium, thorium, and uranium), dielectric measurements, reservoir porosity, gamma ray/reservoir porosity, clay composition/reservoir porosity, etc. It suffices here to state that such correlations faciliLate a continuous computation of CEC and Q v values for a given formation in a geological section or localized area. These techniques, however, all require both well logging and core data over the interval of interest because no single unique mathematical transform can be expected. To overcome these limitations, advanced digital shalysand analysis techniques, such as CLASS and CLAYS, have recently been developed. Based on the WaxmanSmits model and variations in the basic properties of various clay minerals, CLASS and CLAYS analyses provide information on total and effective porosity; total and effective fluid distribution silt volume; amounts, types, and distribution modes of clay minerals present, and reservoir productivity. Details of these methods can be found in Refs. 6 and 7. JPT P. 175^

Clays, Cations, and Geophysical Log Response of Gas-Producing and Nonproducing Zones in the Gammon Shale (Cretaceous), Southwestern North Dakota

AbstractThe Upper Cretaceous Gammon Shale has served as both source bed and reservoir rock for accumulations of natural gas. Gas-producing and nonproducing zones in the Gammon Shale are differentiated on the basis of geophysical log interpretation. To determine the physical basis of the log responses, mineralogical, cation-exchange, textural, and chemical analyses were conducted on core samples from both producing and nonproducing portions of a well in the Gammon Shale from southwestern North Dakota. Statistical treatment (2 sample t-test and discriminant function analysis) of the laboratory data indicate that the producing and nonproducing zones differ significantly in mixed-layer clay content (7 vs. 12%), weight proportion of the clay-size (0.5-1.0 μm) fraction (5.3 vs. 6.3%) ratio of Ca2+ to Na+ extracted during ion exchange (1.4 vs. 1.0), and abundance of dolomite (10 vs. 8%). The geophysical logs apparently record subtle differences in composition and texture which probably reflect variations in the original detrital constituents of the Gammon sediments. Successfully combining log interpretation and clay petrology aids in understanding the physical basis of log response in clay-rich rocks and enhances the effectiveness of logs as predictive geologic tools.