Joint petrophysical interpretation of multidetector nuclear measurements in the presence of invasion, shoulder-bed, and well-deviation effects

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. D13-D30 ◽  
Author(s):  
Edwin Ortega ◽  
Mathilde Luycx ◽  
Carlos Torres-Verdín ◽  
William E. Preeg
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Total Porosity ◽  
Neutron Density ◽  
Layer By Layer ◽  
Fluid Type ◽  
Fluid Properties ◽  
Radial Length ◽  
Neutron Porosity ◽  
Porosity Logs

Recent advances in logging-while-drilling sigma measurements include three-detector thermal-neutron and gamma-ray decay measurements with different radial sensitivities to assess the presence of invasion. We have developed an inversion-based work flow for the joint interpretation of multidetector neutron, density, and sigma logs to reduce invasion, shoulder-bed, and well-deviation effects in the estimation of porosity, water saturation, and hydrocarbon type, whenever the invasion is shallow. The procedure begins with a correction for matrix and fluid effects on neutron and density-porosity logs to estimate porosity. Multidetector time decays are then used to assess the radial length of the invasion and estimate the virgin-zone sigma while simultaneously reducing shoulder-bed and well-deviation effects. Density and neutron porosity logs are corrected for invasion and shoulder-bed effects using two-detector density and neutron measurements with the output from the time-decay (sigma) inversion. The final step invokes a nuclear solver in which corrected sigma, inverse of migration length, and density in the virgin zone are used to estimate water saturation and fluid type. The fluid type is assessed with a flash calculation and Schlumberger’s Nuclear Parameter calculation code to account for the nuclear properties of different types of hydrocarbon and water as a function of pressure, temperature, and salinity. Results indicate that accounting for invasion effects is necessary when using density and neutron logs for petrophysical interpretation beyond the calculation of total porosity. Synthetic and field examples indicate that the mitigation of invasion effects becomes important in the case of salty mud filtrate invading gas-bearing formations. The advantage of the developed inversion-based interpretation method is its ability to estimate layer-by-layer petrophysical, compositional, and fluid properties that honor multiple nuclear measurements, their tool physics, and their associated borehole geometrical and environmental effects.

New Analytical Method To Calculate Matrix- and Fluid-Corrected Total Porosity in Organic Shale

2015 ◽  
Vol 18 (04) ◽  
pp. 609-623
Author(s):  
Edwin Ortega ◽  
Carlos Torres-Verdín
Keyword(s):  
Analytical Method ◽  
Gamma Ray ◽  
Total Porosity ◽  
Matrix Composition ◽  
Neutron Density ◽  
Fluid Density ◽  
Remarkable Feature ◽  
Gamma Ray Spectroscopy ◽  
Porosity Logs ◽  
Organic Shale

Summary Estimation of total porosity from neutron and density porosity logs in organic shale (source rock) is challenging because these logs are substantially affected by fluid and matrix-composition effects. Conventional interpretation of neutron and density porosity logs often includes corrections for shale concentration in which the main objective is to improve the calculation of nonshale porosity in hydrocarbon-bearing zones. These corrections are not desirable in unconventional rock formations because shale pores can be hydrocarbon-saturated. Neutron and density porosity readings across shale zones are sometimes averaged by use of the root-mean-square (RMS) method. We introduce a new and simple analytical expression for total porosity that effectively separates both matrix and fluid effects on neutron and density porosity logs. The expression stems from a new nonlinear mixing law for neutron migration length that is coupled with the linear-density mixing law to calculate total porosity and fluid density. The method is applied in two sequential steps: First, separate corrections for only matrix effects are implemented to enhance the neutron-density crossover for qualitative interpretation of fluid type; second, the coupled equation is used to estimate fluid density and actual porosity devoid of matrix and fluid effects. Calculated porosity and fluid density can be used further to calculate water saturation from density logs. One remarkable feature of this method is the ease with which it can be applied to obtain accurate and reliable results. Application of the method only requires knowledge of single-component nuclear properties and mineral volumetric concentrations. One can obtain nuclear properties from a set of charts for multiple fluid types and minerals provided in this paper, whereas one can calculate mineral concentrations on the basis of available triple combo logs or gamma ray spectroscopy logs. Two synthetic and four field examples (two conventional and two shale-gas reservoirs) are used to test the method. First, we describe an application in a conventional siliciclastic sedimentary sequence in which only shale concentration calculated from gamma ray logs is required to improve the estimation of porosity in shaly sections. Second, we document several applications in which gamma ray spectroscopy logs are used together with a reliable hypothesis for clay type to define mineral properties. Results compare well with nuclear-magnetic-resonance (NMR) and core measurements, whereas the new method outperforms the conventional RMS procedure, especially in the cases of gas-bearing, low-porosity organic shale. The new analytical method can be readily implemented on an Excel spreadsheet and requires minimal adjustments for its operation.

Interpretation of porosity and fluid constituents from well logs using an interactive neutron-density matrix scale

2013 ◽  
Vol 1 (2) ◽  
pp. T143-T155 ◽  
Author(s):  
Olabode Ijasan ◽  
Carlos Torres-Verdín ◽  
William E. Preeg
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Matrix Effects ◽  
Neutron Density ◽  
Reservoir Capacity ◽  
Constant Matrix ◽  
Light Oil ◽  
Saturated Formations ◽  
Neutron Porosity ◽  
Interactive Variable

Neutron and density logs are important borehole measurements for estimating reservoir capacity and inferring saturating fluids. The neutron log, measuring the hydrogen index, is commonly expressed in apparent water-filled porosity units assuming a constant matrix lithology whereby it is not always representative of actual pore fluid. By contrast, a lithology-independent porosity calculation from nuclear magnetic resonance (NMR) and/or core measurements provides reliable evaluations of reservoir capacity. In practice, not all wells include core or NMR measurements. We discovered an interpretation workflow wherein formation porosity and hydrocarbon constituents can be estimated from density and neutron logs using an interactive, variable matrix scale specifically suited for the precalculated matrix density. First, we estimated matrix components from combinations of nuclear logs (photoelectric factor, spontaneous gamma ray, neutron, and density) using Schlumberger’s nuclear parameter calculator (SNUPAR) as a matrix compositional solver while assuming freshwater-filled formations. The combined effects of grain density, volumetric concentration of shale, matrix hydrogen, and neutron lithology units define an interactive matrix scale for correction of neutron porosity. Under updated matrix conditions, the resulting neutron-density crossover can only be attributed to pore volume and saturating fluid effects. Second, porosity, connate-water saturation, and hydrocarbon density are calculated from the discrepancy between corrected neutron and density logs using SNUPAR and Archie’s water saturation equation, thereby eliminating the assumption of freshwater saturation. With matrix effects eliminated from the neutron-density overlay, gas- or light-oil-saturated formations exhibiting the characteristic gas neutron-density crossover become representative of saturating hydrocarbons. This behavior gives a clear qualitative distinction between hydrocarbon-saturated and nonviable depth zones.

scholarly journals Characterization of Mishrif Formation Reservoir in Amara Oil Field, Southeast Iraq, Using Geophysical Well-logging

2021 ◽  
pp. 4702-4711
Author(s):  
Asmaa Talal Fadel ◽  
Madhat E. Nasser
Keyword(s):  
Reservoir Characterization ◽  
Gamma Ray ◽  
Water Saturation ◽  
Total Porosity ◽  
Effective Porosity ◽  
Oil Field ◽  
Neutron Density ◽  
Reservoir Water ◽  
Resistivity Logs ◽  
Reliable Knowledge

     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.   

scholarly journals Petrophysical Properties and Digenetic Evolution of Shuaiba Formation in Nasiriyah Oil Field, Southern Iraq

2021 ◽  
pp. 4810-4818
Author(s):  
Marwah H. Khudhair
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Middle Part ◽  
Effective Porosity ◽  
Oil Field ◽  
Neutron Density ◽  
Petrophysical Properties ◽  
Secondary Porosity ◽  
Primary Porosity ◽  
Gamma Ray Log

     Shuaiba Formation is a carbonate succession deposited within Aptian Sequences. This research deals with the petrophysical and reservoir characterizations characteristics of the interval of interest in five wells of the Nasiriyah oil field. The petrophysical properties were determined by using different types of well logs, such as electric logs (LLS, LLD, MFSL), porosity logs (neutron, density, sonic), as well as gamma ray log. The studied sequence was mostly affected by dolomitization, which changed the lithology of the formation to dolostone and enhanced the secondary porosity that replaced the primary porosity. Depending on gamma ray log response and the shale volume, the formation is classified into three zones. These zones are A, B, and C, each can be split into three rock intervals in respect to the bulk porosity measurements. The resulted porosity intervals are: (I) High to medium effective porosity, (II) High to medium inactive porosity, and (III) Low or non-porosity intervals. In relevance to porosity, resistivity, and water saturation points of view, there are two main reservoir horizon intervals within Shuaiba Formation. Both horizons appear in the middle part of the formation, being located within the wells Ns-1, 2, and 3. These intervals are attributed to high to medium effective porosity, low shale content, and high values of the deep resistivity logs. The second horizon appears clearly in Ns-2 well only.

scholarly journals Petrophysical Properties and Well Log Interpretations of Tertiary Reservoir in Khabaz Oil Field / Northern Iraq

2020 ◽  
Vol 26 (6) ◽  
pp. 18-34
Author(s):  
Yousif Najeeb Abdul-majeed ◽  
Ahmad Abdullah Ramadhan ◽  
Ahmed Jubiar Mahmood
Keyword(s):  
Water Saturation ◽  
Total Porosity ◽  
Effective Porosity ◽  
Oil Field ◽  
Neutron Density ◽  
Petrophysical Properties ◽  
Secondary Porosity ◽  
Northern Iraq ◽  
Sonic Log ◽  
Oil Concentration

The aim of this study is interpretation well logs to determine Petrophysical properties of tertiary reservoir in Khabaz oil field using IP software (V.3.5). The study consisted of seven wells which distributed in Khabaz oilfield. Tertiary reservoir composed from mainly several reservoir units. These units are : Jeribe, Unit (A), Unit (A'), Unit (B), Unit (BE), Unit (E),the Unit (B) considers best reservoir unit because it has good Petrophysical properties (low water saturation and high porous media ) with high existence of hydrocarbon in this unit. Several well logging tools such as Neutron, Density, and Sonic log were used to identify total porosity, secondary porosity, and effective porosity in tertiary reservoir. For Lithological identification for tertiary reservoir units using (NPHI-RHOB) cross plot composed of dolomitic-limestone and mineralogical identification using (M/N) cross plot consist of calcite and dolomite. Shale content was estimated less than (8%) for all wells in Khabaz field. CPI results were applied for all wells in Khabaz field which be clarified movable oil concentration in specific units are: Unit (B), Unit (A') , small interval of Jeribe formation , and upper part of Unit (EB).

Discriminating Shale Layers by Pseudo CGR Logs Created Using Artificial Intelligence

2021 ◽  
Author(s):  
Saud K. Aldajani ◽  
Saud F. Alotaibi ◽  
Abdulazeez Abdulraheem
Keyword(s):  
Artificial Intelligence ◽  
Gamma Ray ◽  
Effective Porosity ◽  
Carbonate Reservoir ◽  
Added Value ◽  
Subtractive Clustering ◽  
Neutron Density ◽  
High Porosity ◽  
Inference System ◽  
Porosity Logs

Abstract The discrimination of shale vs. non-shale layers significantly influences the quality of reservoir geological model. In this study, a novel approach was implemented to enhance the model by creating Pseudo Corrected Gamma Ray (CGR) logs using Artificial Intelligence methods to identify the thin shale beds within the reservoir. The lithology of the carbonate reservoir understudy is mostly composed of dolomite and limestone rock with minor amounts of anhydrite and thin shale layers. The identification of shale layers is challenging because of the nature of such reservoirs. The high organic content of the shales and the presence of dolomites, particularly the floatstones and rudstones, can adversely affect the log quality and interpretation and may result in inaccurate log correlations, overestimating/ underestimating Original Oil In Place (OOIP) and reservoir net pays. In such cases, Corrected Gamma Ray (CGR) curves are typically used to identify shale layers. The CGR curve response is due to the combination of thorium and potassium that is associated with the clay content. The difference between the total GR and the CGR is essentially the amount of uranium-associated organic matter. Because of the very limited number of CGR logs in this reservoir, Artificial Intelligence (AI) approach was used to identify shale volume across the entire reservoir. Synthetic CGR curves were generated for the wells lacking CGR logs using AI methods. Resistivity, Density, Neutron and total GR logs were used as inputs while CGR was set as the target. Five wells that have CGR logs were used to train the model. The created pseudo logs were then used to identify shale layers and could also be used to correct effective porosity logs. After statistical analysis of the data, two different Artificial Intelligence Techniques were tested to predict CGR logs; Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). A Sugeno-type FIS structure using subtractive clustering demonstrated the best prediction with correlation coefficient of 0.96 and mean absolute percentage error (MAPE) of 20%. The resulting synthetic CGR curves helped identify shale layers that do not extend over the entire reservoir area and ultimately correct the effective porosity logs in the reservoir model. Porosity was primarily obtained from the neutron-density logs which results in very high porosity measurements across the shale layers. This study shows a new workflow to predict shale layers in Carbonate reservoirs. The created pseudo CGR logs would help predict shale and is an added-value data that could be incorporated into the Earth model.

scholarly journals Seismic Data Interpretation and Petrophysical Analysis of Kabirwala Area Tola (01) Well, Central Indus Basin, Pakistan

2021 ◽  
Vol 11 (7) ◽  
pp. 2911
Author(s):  
Naveed Ahmad ◽  
Sikandar Khan ◽  
Abdullatif Al-Shuhail
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Research Work ◽  
Total Porosity ◽  
Effective Porosity ◽  
Indus Basin ◽  
Drilling Process ◽  
Reservoir Properties ◽  
Log Data ◽  
Petrophysical Analysis

Well logging is a significant procedure that assists geophysicists and geologists with making predictions regarding boreholes and efficiently utilizing and optimizing the drilling process. The current study area is positioned in the Punjab Territory of Pakistan, and the geographic coordinates are 30020′10 N and 70043′30 E. The objective of the current research work was to interpret the subsurface structure and reservoir characteristics of the Kabirwala area Tola (01) well, which is located in the Punjab platform, Central Indus Basin, utilizing 2D seismic and well log data. Formation evaluation for hydrocarbon potential using the reservoir properties is performed in this study. For the marked zone of interest, the study also focuses on evaluating the average water saturation, average total porosity, average effective porosity, and net pay thickness. The results of the study show a spotted horizon stone with respect to time and depth as follows: Dunghan formation, 0.9 s and 1080.46 m; Cretaceous Samana Suk formation, 0.96 s and 1174.05 m; Datta formation, 1.08 s and 1400 m; and Warcha formation, 1.24 s and 1810 m. Based on the interpretation of well logs, the purpose of petrophysical analysis was to identify hydrocarbon-bearing zones in the study area. Gamma ray, spontaneous potential, resistivity, neutron, and density log data were utilized. The high zone present in the east–west part of the contour maps may be a possible location of hydrocarbon entrapment, which is further confirmed by the presence of the Tola-01 well.

scholarly journals WELL LOGS ANALYSIS TO ESTIMATE THE PARAMETERS OF SAWAN-2 AND SAWAN-3 GAS FIELD

2020 ◽  
Vol 5 (2) ◽  
pp. 69-75
Author(s):  
Raja Asim Zeb ◽  
Muhammad Haziq Khan ◽  
Intikhab Alam ◽  
Ahtisham Khalid ◽  
Muhammad Faisal Younas
Keyword(s):  
Physical Properties ◽  
Oil And Gas ◽  
Water Saturation ◽  
Total Porosity ◽  
Effective Porosity ◽  
Indus Basin ◽  
Log Analysis ◽  
Neutron Density ◽  
Gas Field ◽  
Lower Goru Formation

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.

scholarly journals Petrophysical Analysis of an Iraqi Gas Field (Mansuriya Gas Field)

2020 ◽  
Vol 26 (3) ◽  
pp. 100-116
Author(s):  
Hasan Saleh Azeez ◽  
Dr. Abdul Aali Al-Dabaj ◽  
Dr.Samaher Lazim
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Total Porosity ◽  
Logarithmic Scale ◽  
Formation Factor ◽  
Gas Field ◽  
The Matrix ◽  
Rock Parameters ◽  
Potassium 40

Mansuriya Gas field is an elongated anticlinal structure aligned from NW to SE, about 25 km long and 5-6 km wide. Jeribe formation is considered the main reservoir where it contains condensate fluid and has a uniform thickness of about 60 m. The reservoir is significantly over-pressured, (TPOC, 2014). This research is about well logs analysis, which involves the determination of Archie petrophysical parameters, water saturation, porosity, permeability and lithology. The interpretations and cross plots are done using Interactive Petrophysics (IP) V3.5 software. The rock parameters (a, m and n) values are important in determining the water saturation where (m) can be calculated by plotting the porosity from core and the formation factor from core on logarithmic scale for both and the slope which represent (m) then Pickett plot method is used to determine the other parameters after calculating Rw from water analysis . The Matrix Identification (MID), M-N and Density-Neutron crossplots indicates that the lithology of Jeribe Formation consists of dolomite, limestone with some anhydrite also gas-trend is clear in the Jeribe Formation. The main reservoir, Jeribe Formation carbonate, is subdivided into 8 zones namely  J1 to J8, based mainly on porosity log (RHOB and NPHI) trend, DT trend and saturation trend.  Jeribe formation was considered to be clean in terms of shale content .The higher gamma ray because of the uranium component which is often associated with dolomitisationl and when it is removed and only comprises the thorium and potassium-40 contributions, showed the gamma response to be low compared to the total gamma ray response that also contains the uranium   contribution.While the Jeribe formation is considered to be clean in terms of shale content so the total porosity is equal to the effective porosity.No porosity cut off is found if cutoff permeability 0.01 md is applied while the porosity cut off approximately equal to 0.1 only for unit J6 & J8 if cutoff permeability 0.1 md is applied . It can be concluded that no saturation cutoff for the units of Jeribe formation is found after a cross plot between water saturation and log porosity for the reservoir units of Jeribe formation and applied the calculated cut off porosity. The permeability has been predicted using two methods: FZI and Classical, the two methods yield approximately the same results for all wells.

scholarly journals Shale volume and porosity delineation of coast swamp depobelt in Niger delta region, Nigeria, using well log

2019 ◽  
Vol 7 (2) ◽  
pp. 142
Author(s):  
Ubong Essien
Keyword(s):  
Niger Delta ◽  
Gamma Ray ◽  
Water Saturation ◽  
Effective Porosity ◽  
Neutron Density ◽  
Well Log ◽  
Shale Formations ◽  
Log Data ◽  
Shale Volume ◽  
Niger Delta Region

Well log data from two wells were evaluated for shale volume, total and effective porosity. Well log data were obtained from gamma ray, neutron-density log, resistivity, sonic and caliper log respectively. This study aimed at evaluating the effect of shale volume, total and effective porosity form two well log data. The results of the analysis depict the presence of sand, sand-shale and shale formations. Hydrocarbon accumulation were found to be high in sand, fair in sand-shale and low in shale, since existence of shale reduces total and effective porosity and water saturation of the reservoir. The thickness of the reservoir ranged from 66 – 248.5ft. The average values of volume of shale, total and effective porosity values ranged from 0.004 – 0.299dec, 0.178 – 0.207dec and 0.154 – 0.194dec. Similarly, the water saturation and permeability ranged from 0.277 – 0.447dec and 36.637 - 7808.519md respectively. These values of total and effective porosity are high in sand, fair in sand-shale and low in shale formations. The results for this study demonstrate: accuracy, applicability of these approaches and enhance the proper evaluation of petrophysical parameters from well log data.    

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