Resistivity Logging Response Research Articles

Experimental measurements and response analysis of resistivity of reservoirs with complex wettability: A case study of Yan’an Formation, Ordos Basin, China

Resistivity logs are commonly used to distinguish oil and water reservoirs. However, the complex hydrocarbon accumulation pattern in the study area leads to complex wettability, which significantly affects the resistivity as well as the density and neutron logs and causes difficulties in fluid-type identification. To understand the resistivity characteristics and accurately identify the fluid types, resistivity experiments of core samples selected by the density and neutron logs are performed. The nuclear magnetic resonance (NMR) is simultaneously measured to determine the rock wettability. Instead of the conventional “aged” method for restoring the original wettability, a new set of experimental procedures is developed for obtaining resistivity and NMR [Formula: see text] spectra of samples with wettability as close as possible to that of the original reservoir. Specifically, samples with and without oil washing are measured separately, and a simple correction method for the resistivity index is developed. Moreover, the difference in the water salinity of different wells is considered. The results find that the resistivity index of samples drilled from possible oil-wet reservoirs indicated by the “abnormal” density and neutron responses varied from 2.807 to 5.388, whereas that of possible water-wet reservoirs was less than 2.0. The [Formula: see text] spectra at different states confirm the wettability of the samples. The resistivity index versus saturation ([Formula: see text]–[Formula: see text]) curves of oil-wet rocks are nearly straight lines other than the theoretical concave lines in double-logarithmic coordinates. Oil washing changes the rock wettability to varying degrees. Furthermore, the resistivity log responses of the reservoirs are accurately interpreted using the experimental data. The resistivity is simultaneously affected by the salinity, wettability, and saturation. Finally, based on the factors affecting the reservoir resistivity, fluid identification plots are established for reservoirs with different wettabilities. The agreement rates of identification using the crossplots and oil test are greater than 90%.

A Method for Correction of Shoulder-Bed Effect on Resistivity Logs Based on a Convolutional Neural Network

Abstract —Shoulder beds may have a significant effect on the resistivity log responses. This problem is especially acute in studies of complex strata composed of thin beds with contrasting properties. Different approaches to taking account of the shoulder-bed effect on logging signals are known, such as correction charts, deconvolution operations, and using advanced algorithms of numerical data inversion, which allow one to consider the vertical inhomogeneity of the section. The best result is achieved using the inversion toolkit, but the high labor- and resource-intensiveness of the approach limits its widespread use. The deconvolution approach does not have these disadvantages, but it does not take into account the influence of radial changes in the medium properties on the shapes of measured signals.The possibility of using artificial neural networks (ANN) to increase the vertical resolution of the measured logging data is explored. We assume the existence of a deconvolution-like transformation in which change in the medium properties in the radial direction is also considered. In this case, we can find its approximation using a neural network. The approach is demonstrated by creating a transformation algorithm for the high-frequency electromagnetic logging (VIKIZ) sounding tool, which is widely used in the CIS countries for petroleum exploration. The developed algorithm has been tested on the VIKIZ logs from the Fedorovskoe oilfield (Latitudinal Ob’ region).

Identification of Hydrocarbon Zones and Chimneys Using Seismic Attributes Analysis at Woda Oil Field, Western Offshore Niger Delta

This research investigated hydrocarbon zones and chimneys using seismic attributes analysis in Woda Oil Field, Western offshore Niger Delta. Seismic attributes are powerful tools in monitoring and predicting hydrocarbon zones. Detailed application of seismic attributes on the Woda seismic data aided in the extraction of important information about the geologic features on seismic profiles. Materials used in this research include well logs, seismic data and 3D Post Stack Depth Migration (PSDM) seismic volume. Methods used were seismic attribute analysis and well log interpretation. The reservoirs of interest were identified and analyzed using well log data based on gamma ray, resistivity, and Vp sonic log response. Seismic attributes such as chaos, root mean square velocity, similarity and reflection intensity were quality controlled, enhanced, and generated which assisted in identifying chimneys and hydrocarbon zones. The majority of the chimneys in this research may have nucleated in the lower part of the faulting system below the partially permeable portion of the fault planes and across a regional partially permeable barrier as revealed by thin fault likelihood attribute. Gas expulsion along the lower portion of the complex faulting system perhaps, may have preconfigured the spatial organization of the chimneys. Pockmarks formation above the chimneys as revealed by the sweetness attribute may have inherited the same linear planiform geometry, and both structures recorded the timing of hydrocarbon zones and gas expulsion within the Woda Oil Field.

Enhancing Characterization of Reservoirs Within the Niger Delta Basin Using Integration of Seismic and Well Logs

This research utilized well logs and seismic to unravel the reservoir architecture of a field within the offshore depolbelt of Niger Delta. Gamma ray and resistivity log responses were used for lithology and hydrocarbon reservoirs identifications. The principle of similarity in log signatures was used for correlation across the three studied wells. Pertinent reservoir parameters such as shale volume, effective porosity, permeability, hydrocarbon saturation and water saturation were calculated using well-established equations consistent with the geology. Seismic structural interpretation that will give insight to deformation of the field involves the identification and mapping of faults and horizons from seismic sections. By integrating information from seismic and wells, 3D geological modelling was done using geostatistical methods of Sequential Gaussian Simulation and Indicator. The general stratigraphy of the studied field comprises of intercalation of sands and shales which is typical of Agbada formation. Three reservoirs designated as AA, BB and CC were identified and mapped. Only reservoir CC was laterally continuous across the three wells. Reservoir AA has average shale volume of 13%, effective porosity 26%, hydrocarbon saturation 46% and permeability 1328 mD. Reservoir BB has shale volume of 10%, effective porosity 28%, hydrocarbon saturation 43% and permeability 1616 mD. Reservoir CC has shale volume of 21%, effective porosity 20%, hydrocarbon saturation 89% and permeability 580 mD. Twenty faults comprising of both major and minor faults were mapped. The faults mapped were majorly normal faults. The result of the seismic structural interpretation shows that the probable structures harboring oil and gas are a combination of four-way closure and fault assisted anticlinal structures. The modelling of facies and petrophysical parameters into maps aided the understanding of parameter’s influence on oil and gas production. Reservoir CC has oil and gas in commercial quantities with 2520 MMcf and 622Mbbls respectively. The result shows the reservoir has high performance system and is therefore recommended for development and production. The resulting models will aid placement of production wells and monitoring of future performance of the reservoirs.

Identification of watered-out zones in carbonate reservoirs using resistivity curve reconstruction based on reservoir classification

The KT–II layer in the Zananor Oilfield, Caspian Basin, Kazakhstan, contains carbonate reservoirs of various types. The complex pore structure of the reservoirs have made it difficult to identify watered-out zones with traditional logging interpretation methods. This study classifies the reservoirs on the basis of core analysis and establishes an identification model for watered-out layers in the field to effectively improve the interpretation accuracy. Thin section analysis shows that there are three types of pores in the reservoirs, i.e., the matrix pore, fracture and dissolution vug. A triple porosity model is used to calculate the porosities of the reservoirs and the results are combined with core analysis to classify the reservoirs into the fractured, matrix pore, fracture-pore as well as composite types. A classification standard is also proposed. There are differences in resistivity logging responses from the reservoirs of different types before and after watering-out. The pre–watering-out resistivities are reconstructed using generalized neural network for different types of reservoirs. The watered-out layers can be effectively identified according to the difference in resistivity curves before and after watering-out. The results show that the watered-out layers identified with the method are consistent with measured data, thus serving as a reference for the evaluation of watered-out layers in the study area.

Multimineral petrophysics of thermally immature Eagle Ford Group and Cretaceous mudstones, U.S. Geological Survey Gulf Coast 1 research wellbore in central Texas

Traditional petrophysical methods to evaluate organic richness and mineralogy using gamma-ray and resistivity log responses are not diagnostic in source rocks. We have developed a deterministic, nonproprietary method to quantify formation variability in total organic carbon (TOC) and three key mudrock mineralogical components of nonhydrocarbon-bearing source rock strata of the Eagle Ford Group by developing a set of log-derived multimineral models calibrated with Fourier transform infrared spectroscopy core data from the research borehole U.S. Geological Survey Gulf Coast 1 West Woodway. We determined that bulk density response is a reliable indicator of organic content in these thermally immature, water-bearing source rocks. Multimineral findings indicate that a high degree of laminae-scale mineralogical heterogeneity exists due to thinly interbedded carbonate cements amid clay-rich mudstone layers. The lower part of the Eagle Ford Group contains the highest average TOC content (4.7 wt%) and the highest average carbonate volume (64.1 vol%), making it the optimal target in thermally mature areas for source-rock potential and hydraulic-fracture placement. In contrast, the uppermost portion of the Eagle Ford Group contains the highest average volume of clay minerals (42.6 vol%), which increases the potential for wellbore stability issues. Petrophysical characterization reveals that porosity is approximately 30% in this relatively uncompacted formation. In this thermally immature source rock, water saturation is nearly 100% and no free hydrocarbons were observed on the resistivity logs. No evidence of borehole ellipticity was observed on the three-arm caliper log, and horizontal stresses are presumed to be directionally uniform in the vicinity of this near-surface wellbore. This shallow wellbore has a temperature gradient of 1.87°F/100 ft (16.3°C/km) and is likely influenced by earth surface heating.

Lithology and reservoir properties of the Delaware Mountain Group of the Delaware Basin and implications for saltwater disposal and induced seismicity

ABSTRACTDeepwater siliciclastic deposits of the Delaware Mountain Group (DMG) in the Delaware Basin (DB) are the primary interval for disposal of hydraulic fracturing flowback and produced water from unconventional oil production. Understanding the storage capacity of the DMG is critical in mitigating potential risks such as induced seismicity, water encroachment on production, and drilling hazards, particularly with likely development scenarios and expected volumes of produced water. Here we present a basin-wide geologic characterization of the DMG of the Delaware Basin. The stratigraphic architecture, lithology, and fluid-flow properties including porosity, permeability, amalgamation ratios, and pore volumes, are interpreted and mapped. Lithologies are predicted using gamma-ray and resistivity log responses calibrated to basinal DMG cores and outcrop models. Sandstones exhibit the highest porosity and permeability, and sand depocenters migrate clockwise and prograde basinward throughout Guadalupian time. Permeability is highest at the top of the Cherry and Bell Canyon formations of the DMG, reaching tens to hundreds of millidarcies in porous sandstones. Porous and permeable sandstones are fully amalgamated at the bed scale, but at the channel scale, most sandstones are separated by low-permeability siltstones or carbonates where net sandstone is less than 30%. This geologic characterization can be used to assess the regional storage capacity of the DMG and as input for dynamic fluid-flow models to address pore-pressure evolution, zonal containment, and induced seismicity.

Key factors of marine shale conductivity in southern China—Part I: The influence factors other than porosity

The complicated response mechanism of shale gas requires that a systematic pilot study is conducted on the influences of resistivity log responses to help with subsequent experimental design, physical derivations and resistivity simulations. The purpose of this research is to clarify the main controlling factors of the resistivity log responses and their semi-quantitative relationship in certain marine shale gas formations. Comprehensive analyses on large core test datasets, including mineralogical, petrological, geochemical and other data, from the Longmaxi-Wufeng Formation and the corresponding resistivity logging curves are carried out in 4 shale gas areas. This research indicates that in low-porosity systems, the mineral composition directly impacts the resistivity. Carbonates with large intergranular pores and even intragranular pores increase the resistivity. The hydrophilic nature of clay decreases the resistivity. When organic matter is not carbonized, the organic matter and biosilica will further increase the resistivity. Pyrite layers will cause a large drop in resistivity (to less than 5 Ω m). The resistivity is lower where organic matter carbonization has occurred in the studied reservoir. Mineral components, especially clay minerals and organic matter, are the main controlling factors of the conductivity of low-porosity systems. In addition, we propose that elemental logging can be used to characterize the comprehensive effect of low-porosity s systems on the resistivity of the reservoir and can accurately reflect the resistivity. These results will help to develop future studies on the relationship between the electrical conductivity and saturation of shale gas rocks, which is of great significance. • Combining the data of 14 wells in four shale gas blocks, the resistivity characteristics of marine shale are systematically and quantitatively analysed. • Shale mineral composition is the non-porous factor that mainly affects resistivity, among which carbonate minerals and combinations of biosilica and (uncarbonized) organic matter will increase the resistivity. • The layered pyrite greatly reduces the resistivity, but the dispersed pyrite has little effect on the resistivity of marine shale. • A semi-quantitative characterization technology for non-porous systems is proposed (ER curve), and the effect of mineral composition on resistivity is semi-quantitatively characterized.

A correction method based on geometric factor for resistivity log response of thinly laminated sand reservoirs: A case study

The log response of thin oil layers is greatly subject to environmental factors such as shoulder beds, resulting in errors high enough to influence the appraisal of rock lithology and fluid properties and increasing the difficulty of interpretation of logging curves and the effective evaluation of thinly laminated sand. The development of high-resolution logging instruments and logging curve processing technology improves the resolution and accuracy of logs, but with some limitations. So far, the geometric factor theory has been an effective approximate approach for induction logging correction. Based on the working principle of the induction/resistivity log and on previous studies, we have developed a new model to correct the resistivity log response of thin layers by taking advantage of the geometric factor. This method can improve the accuracy of the resistivity log for the calculation of porosity and water saturation. Our case study indicates that more reliable resistivity can be acquired to better characterize thin layers.

Well-Based Quantitative Reservoir Characterization of Eocene Sokor-1 Formation, Termit Basin, Niger

The Eocene Sokor1 Formation is proven oil reservoir rocks in the Termit sub-basin. These sandstone intervals are deeply buried, highly heterogeneous in character and characterized by Low Contrast Low Resistivity (LCLR) log responses. Petrophysical and quantitative well-based rock physics interpretations were integrated for property estimations, fluid and lithology typing in reservoir characterization. Six (6) reservoir sandstone intervals were identified, delineated and correlated across five (5) wells. The estimated petrophysical properties showed that the Eocene Sokor1 sandstones have averagely good reservoir properties with sand_5 interval exhibiting exceptional reservoir properties. Vp/Vs vs. AI and μρ vs. λρ elastic cross-plots color coded with reservoir properties (Vsh and Φ), show distinct and well separated data clusters signifying hydrocarbon bearing sandstones, brine sandstones and shales/mudstones in the 3D crossplot planes with varying seismic elastic property values in each well thereby, enhancing reservoir characterization and providing information’s about the burial history, reservoir quality and property distribution in the sub-basin. The analysis suggests that, although the reservoir interval has averagely good petrophysical properties in all wells, the seismic elastic crossplots show that these properties are much better distributed in wells 2 and 3 than in wells 4, 5 and 9. Therefore, sand_5 reservoir interval in wells 2 and 3 is likely to be more hydrocarbon bearing and productive than wells 4, 5 and 9 in the sub-basin.

Seismo-Structural Interpretation and Petrophysical Evaluation of Ugwu-Field, Coastal Swamp Depositional Belt of the Niger Delta Basin

Structural interpretation of 3-D seismic data and well log have been applied to unravel hydrocarbon entrapment pattern and petrophysical parameters of X-field within the coastal swamp region of the Niger Delta.. Four reservoir intervals (A, B, C and D) delineated as (W-026, 032, 042 and 048) using gamma ray and resistivity log response. Structural interpretation for inline 5158 revealed four horizons (A, B, C and D) and eight (8) faults labelled (F1, F2, F12, F13, F21, F22, F23, and F24) were mapped. It was observed that the hanging wall block due to reverse drag or rollover anticline slided over fault F12 and created fault F2, thereby creating subsidence where sediments can be deposited. Therefore, faults F2 and F12 created rollover structures which cuts across the entire four reservoirs and invaluably responsible for trapping of hydrocarbon in the field. RMS map developed for horizons ‘A’ and ‘B’ revealed high amplitude anomalies, while variance attribute for both horizons showed relatively uniform lithology observed from east to west across the study area. While from north-east to south west, variance was observed to increase relatively which indicates different lithology. These trend exposes dipping of the channel fill at both flanks by creating extensive faulting. Results of petrophysical evaluation for reservoirs ‘A’ and ‘B’ across the four wells were analyzed. For reservoir ‘A’, porosity values of 32.8%, 24.8%, 25.9% and 27.1% were obtained for wells W-048, 042, 026 and 032 respectively with an average of 27.65%, while for reservoir ‘B’ porosity values of 26.83%, 26.93%, 25.59% and 27.99% for wells W-048, 042, 026 and 032 were obtained respectively with an average of 26.84%. This porosity values were rated very good to excellent for reservoir ‘A’ and very good for reservoir ‘B’, while Permeability values of the order (K > 1000mD) were obtained for both reservoirs across the four wells and is rated excellent. Hydrocarbon saturation (Shc) across the four wells averages at 68.57% for reservoir ‘A’ and 68.67% for reservoir ‘B’ which is high. Log motifs using gamma ray log for well-026 was integrated with seismic facies to infer on depositional environment of the reservoirs horizons showed a combination of serrated funnel/blocky shape log response and coarsening upward cycles. For reservoirs ‘A’, ‘B’ and ‘C’ the log shape pattern indicates deposition in a fluvial / tidal, channel environment while for reservoir ‘D’ the pattern indicates deposition in deltaic front environment. Isochore maps computed for horizons ‘A’ and ‘B’, shows that horizon ‘A’ is relatively thick and this pattern suggests increased tectonic activities during deposition of reservoir ‘A’ and is an indication that reservoir ‘A’ is a synrift deposit. 
 Keywords: 3-D Seismic interpretation, Faults, Seismostratigraphy, Well log, Seismic Attributes, Petrophysical parameters

Resistivity dispersion in pyrite-bearing shaly sandstones

In pyrite-bearing shaly sandstones, the distortion in the resistivity logging response of formations in high-frequency resistivity logging because of dispersion hinders the calculation of reservoir saturation. To eliminate the effect of resistivity dispersion of pyrite and shale, and to avoid factors, such as mineral composition, content, and distribution in natural cores, we synthesized twelve samples with dispersed pyrite and shale grains at high temperature and pressure (60 MPa and 120 °C). We performed experiments at different water salinities and oil saturations, and different frequency to assess the effect of frequency on the conductivity of pyrite-bearing shaly sandstones. Both the dispersed pyrite and shale grains show dispersion, and the real part of the complex resistivity decreases with increasing frequency. Based on symmetrical effective medium conductivity theory and the experimental data, the effective medium dispersion model for the real part of the complex resistivity for pyrite-bearing shaly sandstones is established considering the effect of pyrite and shale content on resistivity dispersion. Simulations suggest that the predicted resistivity dispersion by the model in pyrite-bearing shaly sandstones for variable frequency, and pyrite and shale content agrees with the experimental results. The proposed model can successfully predict the dispersion of pyrite-bearing shaly sandstones. Finally, the resistivity dispersion correction plot for the conductivity of pyrite and shale grains of 0.062 S/m and 0.031 S/m, respectively, is established based on the frequency applied to various electric logs, and the correction method for the high-frequency resistivity log response is given to obtain the real formation resistivity.

Resistivity Logging Through Casing Response of Inclined Fractured Formation

The calculation of resistivity logging response (RLR) of the microfracture has always been a challenge in formation evaluation in different scales. The transmission line equation (TLE) has been proven to be effective in solving the apparent resistivity of formation in the resistivity logging through casing. However, the existing algorithms are not suitable to calculate the RLR of fractured formation through casing. A new method is proposed to calculate the transverse resistance in the inclined fractured formation by using the TLE and current flux tube model. In the case when inclined fractures are not intersected with the casing, an analytic expression of the transverse resistance is derived. However, in the case where inclined fractures intersect with the casing, the transverse resistance of intersection can be calculated numerically through simplifying from the double integral to single integral. The validity tests show that the transverse resistance and apparent resistivity calculated with this proposed method have excellent match with the analytical solutions in the case of homogenous infinite formation. In addition, the apparent resistivity of formation increases with the decrease of fracture dipping angle. The existence of inclined fracture with highly resistant fluid affects the RLR significantly.

CHARACTERIZATION OF THE HYDROCARBON POTENTIAL AND NON-POTENTIAL ZONES USING WAVELET-BASED FRACTAL ANALYSIS

The identification of prospective and dry zone is of major importance from well log data. Truthfulness in the identification of potential zone is a very crucial issue in hydrocarbon exploration. In this line, the problem has received considerable attention and many conventional techniques have been proposed. The purpose of this study is to recognize the hydrocarbon and non-hydrocarbon bearing portion within a reservoir by using the non-conventional technique. The wavelet based fractal analysis (WBFA) has been applied on the wire-line log data in order to obtain the pre-defined hydrocarbon (HC) and non-hydrocarbon (NHC) zones by their self-affine signal nature is demonstrated in this paper. The feasibility of the proposed technique is tested with the help of most commonly used logs, like self-potential, gamma ray, resistivity and porosity log responses. These logs are obtained from the industry to make out several HC and NHC zones of all wells in the study region belonging to the upper Assam basin. The results obtained in this study for a particular log response, where in the case of HC bearing zones, it is found that they are mainly situated in a variety of sandstones lithology which leads to the higher Hurst exponent. Further, the NHC zones found to be analogous to lithology with higher shale content having lower Hurst exponent. The above proposed technique can overcome the chance of miss interpretation in conventional reservoir characterization.

Petro physical properties analysis of beani bazar gas field, Bangladesh using wireline log interpretation

The study on analysis of petro physical properties which are done into two well such as BB-1 and BB-2 of Beani Bazar Gas Field using wire line log data. In BB-1, Upper Gas Sand (UGS), Lower Gas Sand (LGS), Sand-1 and Bellow Lower Gas Sand (BLGS) zones and in BB-2, UGS and LGS are identified through high gamma ray log, high resistivity, low neutron and low density log response. The thickness of UGS, LGS, Sand-1, BLGS of BB-1 and UGS, LGS of BB-2 are respectively 47.69m, 14.326m, 17.526m, 17.526m and 26.37m, 21.03m. The Shale volumes of UGS, LGS, Sand-1 and BLGS of BB-1 are respectively 14.87%, 21.58%, 11.69% and 21.28% and UGS and LGS of BB-2 are respectively 17.91% and 29.33%, which are measured through Schlumberger Clavier method. The average porosity of UGS, LGS, Sand-1 and BLGS of BB-1 are respectively 17.55%, 16.60%, 18.07% and 31.10% and UGS and LGS of BB-2 are respectively 13.19% and 11.29%, which are very effective for hydrocarbon prospect by using neutron-density combination method. The average water saturations of UGS, LGS, Sand-1 and BLGS of BB-1 are respectively 24.97%, 23.78%, 80.18% and 19.85% which revised to hydrocarbon saturations as respectively 75.03%, 76.22%, 19.82% and 80.15% and UGS and LGS of BB-2 are respectively 41.20% and 69.50% which revised to hydrocarbon saturations as respectively 58.80% and 30.50% that are followed by Simandoux method. By analysis of petro physical properties of those zones, the UGS and LGS are very effective hydrocarbon bearing zones where production is running at the present time, the Sand-1 zone is water bearing zone. This study impose high important on BLGS. This zone is satisfied all criteria for hydrocarbon prospect. This study recommends that more study is needed for BLGS, and it may be commercially economical viable in a future.

Integrated core-log facies analysis and depositional model of the gas hydrate-bearing sediments in the northeastern continental slope, South China Sea

Host sediments may exert a significant influence on the formation of gas hydrate reservoirs. However, this issue has been largely neglected in the literature. In this study, we investigated the types, characteristics and the depositional model of the fine-grained gas hydrate-bearing sediments in the northeastern margin of the South China Sea by integrating core visual observations and logging-while-drilling downhole logs. The gas hydrate-bearing sediments consist dominantly of muddy sediments formed in the inter-canyon ridges of the upper continental slope, including hemipelagites, debrites (mud with breccia) and fine-grained turbidites. Cold-seep carbonates and associated slumping talus, muddy breccia debrites, as well as coarse-grained turbidites, may locally occur. Four classes and six sub-classes of log facies were defined by cluster analysis. Core-log correlation indicates that gas hydrates are majorly distributed in fine-grained sediments with high resistivity and low acoustic transit time (AC) log responses, which are easily differentiated from the fine-grained background sediments of high gamma-ray (GR), high AC, and low resistivity log values, and the seep carbonates characterized by low GR, high resistivity, high density, low AC and low porosity log values. The primary host sediments consist of fine-grained hemipelagic sediments formed by deposition from the nepheloid layers of river material and from the microfossils in seawater column. Most of the hemipelagic sediments, however, might have been extensively modified by slumping and associated gravity flow processes and were re-deposited in the forms of debrites and turbidites. Locally developed seep carbonates associated with gas hydrate dissociation and leakage provided additional sources for the gravity flow sediments.

Dual-shale-content method for total organic carbon content evaluation from wireline logs in organic shale

AbstractOrganic shale is one of the most important unconventional resources all around the world. Total organic carbon (TOC) content is an important evaluation parameter of reservoir hydrocarbon source quality. The regular evaluation methods have higher requirements of well logs and core experiment data for statistical regression. Through analyzing the resistivity and gamma ray logging response characteristics of shale content and organic matters, combined with digital rock physics experiment simulation, we put forward and improve the dual-shale-content method for TOC content logging evaluation. The accuracy of this method is verified by actual data processing. The result shows the dual-shale-content method is simple to use and the error is small. And by comparing with the calculation results by using the

Improving prediction of Total Organic Carbon in prospective Australian basins by employing machine learning

Total organic carbon (TOC) is directly associated with total porosity and gas content and is a critical factor in assessing the potential of unconventional reservoirs. TOC content is only known at the depths where the laboratory measurements on recovered core samples are performed. However, reliable estimation of potential resources can only be based on information about vertical and lateral distribution of organic matter throughout the prospective gas shale reservoir. This information is commonly obtained from conventional wireline logs, such as gamma ray, density, transit time and resistivity. Due to the complexity of unconventional reservoirs, traditional methods based on distinct differences of resistivity, density and sonic velocity of organic matter from those of the inorganic matrix are not always successful. We investigate the best way to predict the TOC using gamma-ray, density, porosity, resistivity and sonic transit time log responses by applying machine learning methods such as Artificial Neural Network (ANN) and Support Vector Machine (SVM). The analysis is done on the data from seven wells drilled through onshore unconventional reservoirs in the McArthur Basin (Northern Territory) and Georgina Basin (Northern Territory and Queensland), Australia. The prediction quality of traditional, multiple liner regression (MLR) and machine learning methods was compared. The most accurate TOC estimates were generated by ANN- and SVM-based nonlinear predictors, followed by the MLR and traditional models. This indicates that geologic complexity affects the relationship between the log response and TOC in the area of interest.

A new correlation for water saturation calculation in gas shale reservoirs based on compensation of kerogen-clay conductivity

Determination of water saturation in gas shale reservoirs is a very challenging issue due to the incomplete understanding of the non-Archie components. Kerogen and clay content are the two main factors controlling the conductivity of gas shales and resistivity log responses. The presence of clays as conductive materials causes excessive conductivity for the rock that result in an overestimation of water saturation calculation. On the other hand, the presence of solid kerogen has an opposite effect to clays and causes reduction of rock conductivity and thus underestimation of water saturation.In this research, attempts have been made to develop an effective equation for water saturation determination in gas shale reservoirs based on compensation of kerogen and shale conductivities. The new equation is able to handle both high and low conductivity components. The proposed approach makes one step ahead towards reducing uncertainty in the petrophysical evaluation of gas shale reservoirs. Being independent of formation water resistivity and Archie parameters are of the important and effective aspects of the introduced equation in water saturation calculation of gas shale reservoirs.Finally, the kerogen-clay compensation equation has successfully been applied to the determination of water saturation in the Goldwyer shale formation, Canning basin, Western Australia.

Identification of formation interfaces by using wavelet and Fourier transforms

The identification of formation interfaces is of prime importance from well log data. The interfaces are not clearly discernible due to the presence of high and low frequency noise in the log response. Accurate bed boundary information is very crucial in hydrocarbon exploration and the problem has received considerable attention and many techniques have been proposed. Frequency spectrum based filtering techniques aids us in interpretation, but usually leads to inaccurate amplification of unwanted components of the log response. Wavelet transform is very effective in denoising the log response and can be carried out to filter low and high frequency components of signal. The use of Fourier and Wavelet transform in denoising the log data for obtaining formation interfaces is demonstrated in this work. The feasibility of the proposed technique is tested so that it can be used in the industry to decipher formation interfaces. The work flow is demonstrated by testing on wells belonging to the Upper Assam Basin, which are self-potential, gamma ray, and resistivity log responses.