scholarly journals Depositional facies model and reservoir characterization of USANI field 1, Niger delta basin, Nigeria

2017 ◽  
Vol 5 (2) ◽  
pp. 57 ◽  
Author(s):  
Godwin Aigbadon ◽  
A.U Okoro ◽  
Chuku Una ◽  
Ocheli Azuka

The 3-D depositional environment was built using seismic data. The depositional facies was used to locate channels with highly theif zones and distribution of various sedimentary facies. The integration core data and the gamma ray log trend from the wells within the studied interval with right boxcar/right bow-shape indicate muddy tidal flat to mixed tidal flat environments. The bell–shaped from the well logs with the core data indicate delta front with mouth bar, the blocky box- car trend from the well logs with the core data indicate tidal point bar with tidal channel fill. The integration of seismic to well log tie display a good tie in the wells across the field. The attribute map from velocity analysis revealed the presence of hydrocarbons in the identified sands (A, B, C, D1, D2, D4, D5). The major faults F1, F2, F3 and F4 with good sealing capacity are responsible for hydrocarbon accumulation in the field. Detailed petro physical analysis of well log data showed that the studied interval are characterized by sand-shale inter-beds. Eight reservoirs were mapped at depth intervals of 2886m to 3533m with their thicknesses ranging from 12m to 407m. Also the Analysis of the petrophysical results showed that porosity of the reservoirs range from 14% to 28 %; permeability range from 245.70 md to 454.7md; water saturation values from 21.65% to 54.50% and hydrocarbon saturation values from 45.50% to 78.50 %. The by-passed hydrocarbons were identified and estimated in low resistivity pay sands D1, D2 at depth of 2884m – 2940m, sand D5 at depth of 3114m – 3126m respectively. The model serve as a basis for establishing facies model in the field.

2007 ◽  
Vol 10 (06) ◽  
pp. 711-729 ◽  
Author(s):  
Paul Francis Worthington

Summary A user-friendly type chart has been constructed as an aid to the evaluation of water saturation from well logs. It provides a basis for the inter-reservoir comparison of electrical character in terms of adherence to, or departures from, Archie conditions in the presence of significant shaliness and/or low formation-water salinity. Therefore, it constitutes an analog facility. The deliverables include reservoir classification to guide well-log analysis, a protocol for optimizing the acquisition of special core data in support of log analysis, and reservoir characterization in terms of an (analog) porosity exponent and saturation exponent. The type chart describes a continuum of electrical behavior for both water and hydrocarbon zones. This is important because some reservoir rocks can conform to Archie conditions in the fully water-saturated state, but show pronounced departures from Archie conditions in the partially water-saturated state. In this respect, the chart is an extension of earlier approaches that were restricted to the water zone. This extension is achieved by adopting a generalized geometric factor—the ratio of water conductivity to formation conductivity—regardless of the degree of hydrocarbon saturation. The type chart relates a normalized form of this geometric factor to formation-water conductivity, a "shale" conductivity term, and (irreducible) water saturation. The chart has been validated using core data from comprehensively studied reservoirs. A workflow details the application of the type chart to core and/or log data. The analog role of the chart is illustrated for reservoir units that show different levels of non-Archie effects. The application of the method should take rock types, scale effects, the degree of core sampling, and net reservoir criteria into account. The principal benefit is a reduced uncertainty in the choice of a procedure for the petrophysical evaluation of water saturation, especially at an early stage in the appraisal/development process, when adequate characterizing data may not be available. Introduction One of the ever-present problems in petrophysics is how to carry out a meaningful evaluation of well logs in situations where characterizing information from quality-assured core analysis is either unavailable or is insufficient to satisfactorily support the log interpretation. This problem is especially pertinent at an early stage in the life of a field, when reservoir data are relatively sparse. Data shortfalls could be mitigated if there was a means of identifying petrophysical analogs of reservoir character, so that the broader experience of the hydrocarbon industry could be utilized in constructing reservoir models and thence be brought to bear on current appraisal and development decisions. Here, a principal requirement calls for type charts of petrophysical character, on which data from different reservoirs can be plotted and compared, as a basis for aligning approaches to future data acquisition and interpretation. This need manifests itself strongly in the petrophysical evaluation of water saturation, a process that traditionally uses the electrical properties of a reservoir rock to deliver key building blocks for an integrated reservoir model. The solution to this problem calls for an analog facility through which the electrical character of a subject reservoir can be compared with others that have been more comprehensively studied. In this way, the degree of confidence in log-derived water saturation might be reinforced. At the limit, the log analyst needs a reference basis for recourse to capillary pressure data in cases where the well-log evaluation of water saturation turns out to be prohibitively uncertain.


2019 ◽  
Vol 7 (1) ◽  
pp. 58
Author(s):  
G. O. Aigbadon ◽  
E. O. Akpunonu ◽  
S. O. Agunloye ◽  
A. Ocheli ◽  
O. O .Akakaru

This study was carried out integrating well logs and core to build reservoir model for the Useni-1 oil field. Core data and well logs were used to evaluate the petrophysical characteristics of the reservoirs. The paleodepositional environment was deduce from the wells and cores data. The depositional facies model showed highly permeable channels where the wells where positioned. The environments identified that the fluvial channel facies with highly permeable zones constituted the reservoirs. Four reservoirs were mapped at depth range of 8000ft to 8400ft with thicknesses varying from 20ft to 400ft. Petrophysical results showed that porosity of the reservoirs varied from 12% to 28 %; permeability from 145.70 md to 454.70md; water saturation from 21.65% to 54.50% and hydrocarbon saturation from 45.50% to 78.50 %. Core data and the gamma ray log trends with right boxcar trend indicate fluvial point bar and tidal channel fills in the lower delta plain setting. By-passed hydrocarbons were identified in low resistivity pay sands D1, D2 at depth of 7800 – 78100ft in the field.  


2021 ◽  
Author(s):  
Zulkuf Azizoglu ◽  
Zoya Heidari ◽  
Leonardo Goncalves ◽  
Lucas Abreu Blanes De Oliveira ◽  
Moacyr Silva Do Nascimento Neto

Abstract Broadband dielectric dispersion measurements are attractive options for assessment of water-filled pore volume, especially when quantifying salt concentration is challenging. However, conventional models for interpretation of dielectric measurements such as Complex Refractive Index Model (CRIM) and Maxwell Garnett (MG) model require oversimplifying assumptions about pore structure and distribution of constituting fluids/minerals. Therefore, dielectric-based estimates of water saturation are often not reliable in the presence of complex pore structure, rock composition, and rock fabric (i.e., spatial distribution of solid/fluid components). The objectives of this paper are (a) to propose a simple workflow for interpretation of dielectric permittivity measurements in log-scale domain, which takes the impacts of complex pore geometry and distribution of minerals into account, (b) to experimentally verify the reliability of the introduced workflow in the core-scale domain, and (c) to apply the introduced workflow for well-log-based assessment of water saturation. The dielectric permittivity model includes tortuosity-dependent parameters to honor the complexity of the pore structure and rock fabric for interpretation of broadband dielectric dispersion measurements. We estimate tortuosity-dependent parameters for each rock type from dielectric permittivity measurements conducted on core samples. To verify the reliability of dielectric-based water saturation model, we conduct experimental measurements on core plugs taken from a carbonate formation with complex pore structures. We also introduce a workflow for applying the introduced model to dielectric dispersion well logs for depth-by-depth assessment of water saturation. The tortuosity-dependent parameters in log-scale domain can be estimated either via experimental core-scale calibration, well logs in fully water-saturated zones, or pore-scale evaluation in each rock type. The first approach is adopted in this paper. We successfully applied the introduced model on core samples and well logs from a pre-salt formation in Santos Basin. In the core-scale domain, the estimated water saturation using the introduced model resulted in an average relative error of less than 11% (compared to gravimetric measurements). The introduced workflow improved water saturation estimates by 91% compared to CRIM. Results confirmed the reliability of the new dielectric model. In application to well logs, we observed significant improvements in water saturation estimates compared to cases where a conventional effective medium model (i.e., CRIM) was used. The documented results from both core-scale and well-log-scale applications of the introduced method emphasize on the importance of honoring pore structure in the interpretation of dielectric measurements.


2021 ◽  
Vol 54 (2E) ◽  
pp. 186-197
Author(s):  
Maan Al-Majid

The Early Miocene Euphrates Formation is characterized by its oil importance in the Qayyarah oil field and its neighboring fields. This study relied on the core and log data analyses of two wells in the Qayyarah oil field. According to the cross-plot’s information, the Euphrates Formation is mainly composed of dolomite with varying proportions of limestone and shale. Various measurements to calculate the porosity, permeability, and water saturation on the core samples were made at different depths in the two studied wells Qy-54 and Qy-55. A relationship between water saturation and capillary pressure has been plotted for some core samples to predict sites of normal compaction in the formation. The line regression for this relationship was considered as a function of the ratio of large voids to the total volume of voids in the sample. The coefficient of determination parameter was used in estimating the amount of homogeneity in the sizes of the voids, as it was observed to increase significantly at the sites of shale. After dividing the formation into several zones, the well log data were analyzed to predict the locations of oil presence in both wells. The significance of the negative secondary porosity in detecting the hydrocarbon sites in the Euphrates Formation was deduced by its correspondence with the large increase in the true resistivity values in both wells. More than 90% of the formation parts represent reservoir rocks in both wells, but only about 75% of them are oil reservoirs in the well Qy-54 and nearly 50% of them are oil reservoirs in the well Qy-55.


2013 ◽  
Vol 321-324 ◽  
pp. 2444-2447
Author(s):  
Cheng Hua Ou ◽  
Qiang Han ◽  
Wen Jiang Zhou

There are more and more overseas offshore oil project in china, along of external interdependent level in petroleum becomes upgrading year by year. Therefore, developing quick forecast method on overseas offshore reservoirs becomes very necessary. The method is divided into three steps: i the core data analysis results are used to calibrate the interpretation about logs of well, ii the well log interpreted results are used to mark seismic data, iii the abundant seismic data is used to forecast overseas offshore reservoir quickly. And rear end in this article, an overseas offshore reservoir is used to as an example to verify the applicability and reliability of the method.


2021 ◽  
Author(s):  
Elias R. Acosta ◽  
◽  
Bhagwanpersad Nandlal ◽  
Ryan Harripersad ◽  
◽  
...  

This research proposed an alternative method for determining the saturation exponent (n) by finding the best correlations for the heterogeneity index using available core data and considering wettability changes. The log curves of the variable n were estimated, and the effect on the water saturation (Sw) calculations and the Stock Tank Oil Initially In Place (STOIIP) in the Tambaredjo (TAM) oil field was analyzed. Core data were employed to obtain the relationship between n and heterogeneity using cross-plots against several heterogeneity indices, reservoir properties, and pore throat size. After filtering the data, the clay volume (Vcl), shale volume, silt volume, basic petrophysical property index (BPPI), net reservoir index, pore grain volume ratio, and rock texture were defined as the best matches. Their modified/improved equations were applied to the log data and evaluated. The n related to Vcl was the best selection based on the criteria of depth variations and logical responses to the lithology. The Sw model in this field showed certain log readings (high resistivity [Rt] reading ≥ 500 ohm.m) that infer these intervals to be probable inverse-wet (oil-wet). The cross-plots (Rt vs. Vcl; Rt vs. density [RHOB]; Rt vs. total porosity [PHIT]) were used to discard the lithologies related to a high Rt (e.g., lignites and calcareous rocks) and to correct Sw when these resulted in values below the estimated irreducible water saturation (Swir). The Sw calculations using the Indonesian equation were updated to incorporate n as a variable (log curves), comparing it with Sw from the core data and previous calculations using a fixed average value (n = 1.82) from the core data. An integrated approach was used to determine n, which is related to the reservoir’s heterogeneity and wettability changes. The values of n for high Rt (n > 2) intervals ranged from 2.3 to 8.5, which is not close to the field average n value (1.82). Specific correlations were found by discriminating Swir (Swir < 15%), (Swir 15%–19%), and Swir (> 19%). The results showed that using n as a variable parameter improved Sw from 39.5% to 36.5% average in the T1 and T2 sands, showing a better fit than the core data average and increasing the STOIIP estimations by 6.81%. This represents now a primary oil recovery of 12.1%, closer to the expected value for these reservoirs. Although many studies have been done on n determination and its effect on Sw calculations, using average values over a whole field is still a common practice regardless of heterogeneity and wettability considerations. This study proposed a method to include the formation of heterogeneity and wettability changes in n determination, allowing a more reliable Sw determination as demonstrated in the TAM oil field in Suriname.


2013 ◽  
Vol 1 (1) ◽  
pp. T113-T123 ◽  
Author(s):  
Zoya Heidari ◽  
Carlos Torres-Verdín

Reliable estimates of petrophysical and compositional properties of organic shale are critical for detecting perforation zones or candidates for hydro-fracturing jobs. Current methods for in situ formation evaluation of organic shale largely rely on qualitative responses and empirical formulas. Even core measurements can be inconsistent and inaccurate when evaluating clay minerals and other grain constituents. We implement a recently introduced inversion-based method for organic-shale evaluation from conventional well logs. The objective is to estimate total porosity, total organic carbon (TOC), and volumetric/weight concentrations of mineral/fluid constituents. After detecting bed boundaries, the first step of the method is to perform separate inversion of individual well logs to estimate bed physical properties such as density, neutron migration length, electrical conductivity, photoelectric factor (PEF), and thorium, uranium , and potassium volumetric/weight concentrations. Next, a multilayer petrophysical model specific to organic shale is constructed with an initial guess obtained from conventional well-log interpretation or X-ray diffraction data; bed physical properties are calculated with the initial layer-by-layer values. Final estimates of organic shale petrophysical and compositional properties are obtained by progressively minimizing the difference between calculated and measured bed properties. A unique advantage of this method is the correction of shoulder-bed effects on well logs, which are prevalent in shale-gas plays. Another advantage is the explicit calculation of accurate well-log responses for specific petrophysical, mineral, fluid, and kerogen properties based on chemical formulas and volumetric concentrations of minerals/kerogen and fluid constituents. Examples are described of the successful application of the new organic-shale evaluation method in the Haynesville shale-gas formation. This formation includes complex solid compositions and thin beds where rapid depth variations of mineral/fluid constituents are commonplace. Comparison of estimates for total porosity, total water saturation, and TOC obtained with (a) commercial software for multimineral analysis, (b) our organic-shale evaluation method, and (c) core/X-ray diffraction measurements indicates a significant improvement in estimates of total porosity and water saturation yielded by our interpretation method. The estimated TOC is also in agreement with core laboratory measurements.


Author(s):  
Adel Alabeed ◽  
Zeyad Ibrahim ◽  
Emhemed Alfandi

A reservoir is a subsurface rock that has effective porosity and permeability which usually contains commercially exploitable quantity of hydrocarbon. Reservoir characterization is undertaken to determine its capability to both store and transmit fluid. Petrophysical well log and core data, in this paper, were integrated in an analysis of the reservoir characteristics by selecting of three productive wells. The selected wells are located at Abu Attifel field in Libya for Upper Nubian Sandstone formation at depth varied form 12921 to14330 ft. The main aim of this study is to compare the laboratory measurement of core data with that obtained from well log data in order to determine reservoir properties such as shale volume, porosity (Φ), permeability (K), fluid saturation, net pay thickness. The plots of porosity logs and core porosity versus depth for the three wells revealed significant similarity in the porosity values. The average volume of shale for the reservoir was determined to be 22.5%, and average permeability values of the three wells are above 150 md, while porosity values ranged from 9 to 11%. Low water saturation 13 to 22% in the three wells indicates the wettability of the reservoir is water-wet.


2020 ◽  
Vol 10 (17) ◽  
pp. 5940
Author(s):  
Touhid Mohammad Hossain ◽  
Junzo Watada ◽  
Izzatdin A. Aziz ◽  
Maman Hermana

Initially, electrofacies were introduced to define a set of recorded well log responses in order to characterize and distinguish a bed from the other rock units, as an advancement to the conventional application of well logs. Well logs are continuous records of several physical properties of drilled rocks that can be related to different lithologies by experienced log analysts. This work is time consuming and likely to be imperfect because human analysis is subjective. Thus, any automated classification approach with high promptness and accuracy is very welcome by log analysts. One of the crucial requirements in petroleum engineering is to interpret a bed’s lithology, which can be done by grouping a formation into electrofacies. In the past, geophysical modelling, petro-physical analysis, artificial intelligence and several statistical method approaches have been implemented to interpret lithology. In this research, important well log features are selected by using the Extra Tree Classifier (ETC), and then five individual electrofacies are constructed by using the selected well log features. Finally, a rough set theory (RST)-based whitebox classification approach is proposed to classify the electrofacies by generating decision rules. These rules are later on used to determine the lithology classes and we found that RST is beneficial for performing data mining tasks such as data classification and rule extraction from uncertain and vague well log datasets. A comparison study is also provided, where we use support vector machine (SVM), deep learning based on feedforward multilayer perceptron (MLP) and random forest classifier (RFC) to compare the electrofacies classification accuracy.


Author(s):  
Ahmad Muraji Suranto ◽  
Aris Buntoro ◽  
Carolus Prasetyadi ◽  
Ricky Adi Wibowo

In modeling the hydraulic fracking program for unconventional reservoir shales, information about elasticity rock properties is needed, namely Young's Modulus and Poisson's ratio as the basis for determining the formation depth interval with high brittleness. The elastic rock properties (Young's Modulus and Poisson's ratio) are a geomechanical parameters used to identify rock brittleness using core data (static data) and well log data (dynamic data). A common problem is that the core data is not available as the most reliable data, so well log data is used. The principle of measuring elastic rock properties in the rock mechanics lab is very different from measurements with well logs, where measurements in the lab are in high stresses / strains, low strain rates, and usually drained, while measurements in well logging use the principle of measured downhole by high frequency sonic. vibrations in conditions of very low stresses / strains, High strain rate, and Always undrained. For this reason, it is necessary to convert dynamic to static elastic rock properties (Poisson's ratio and Young's modulus) using empirical equations. The conversion of elastic rock properties (well logs) from dynamic to static using the empirical calculation method shows a significant shift in the value of Young's Modulus and Poisson's ratio, namely a shift from the ductile zone dominance to the dominant brittle zone. The conversion results were validated with the rock mechanical test results from the analog outcrop cores (static) showing that the results were sufficiently correlated based on the distribution range.


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