Petrophysical Model Research Articles

Method of Geomechanical Parameter Determination and Volumetric Fracturing Factor Simulation under Highly Stochastic Geologic Conditions

In order to accurately predict geomechanical parameters of oil-bearing reservoirs and influencing factors of volumetric fracturing, a new method of geomechanical parameter prediction combining seismic inversion, well logging interpretation and production data is proposed in this paper. Herein, we present a structure model, petrophysical model and geomechanical model. Moreover, a three-dimensional geomechanical model of a typical reservoir was established and corrected using history matching. On this basis, a typical well model was established, 11 influencing factors of volume fracturing including formation parameters and fracturing parameters were analyzed and their impact were ranked, and the oil recovery rate and the accumulated oil production before and after optimal fracturing were compared. The results show that with respect to formation parameters, reservoir thickness is the main influencing factor; interlayer thickness and stress difference are the secondary influencing factors; and formation permeability, Young’s modulus and Poisson’s ratio are the weak influencing factors. For a pilot well of a typical reservoir, the optimized fracture increased production by 7 tons/day relative to traditional fracturing. After one year of production, the method increased production by 4 tons/day relative to traditional fracturing, showing great potential in similar oil reservoirs.

Petrophysical modeling of rocks dominik formation as the basis of interpretation of seismic data

The paper is devoted to theoretical modeling of effective elastic properties of rock samples of domanik deposits. To determine the effective elastic properties of rocks, depending on their composition and morphological characteristics, the methods of effective medium theory were used. The aim of the work was to determine the parameters characterizing the microstructure of the investigated rock samples; creation of a seismic-geological model and calculation of reflection coefficients for it. The main attention in the work is paid to the influence of the content of kerogen and the degree of its maturity (porosity) on the measured physical quantities (velocities of elastic waves, reflection coefficients).

Reservoir multiparameter prediction method based on deep learning for CO2 geologic storage

Time-lapse seismic difference refers to the comprehensive response of fluid saturation, pore pressure, and porosity. However, the contribution of different parameters to the seismic response is difficult to distinguish. The high-precision prediction of these reservoir parameters is of great significance in CO2 geologic storage and oil and gas development. Therefore, a simultaneous time-lapse reservoir multiparameter prediction method based on a multitask learning network is proposed. Combined with CO2 geologic storage monitoring, the process of generating training data is described, involving numerical simulation, petrophysical models, and seismic forward modeling. Moreover, the Hertz-Mindlin formula, which considers pressure changes, is used to establish the relationship between formation elasticity and physical parameters in CO2 storage. The effects of fluid saturation, pressure, and porosity on P- and S-wave velocities and densities are analyzed, and the amplitude-variation-with-offset response characteristics of fluid saturation, pressure, and porosity changes are discussed. In total, 4700 and 300 sets of reservoir parameters and seismic angle gather data are used for network training and testing, respectively. The prediction results of synthetic and field data find that the time-lapse reservoir multiparameter prediction method based on multitask learning can effectively distinguish changes in each parameter and simultaneously obtain high-precision prediction results of fluid saturation, pressure, and porosity. Once the network is constructed, the prediction will take only a few seconds, which will promote the further development of the CO2 geologic storage theory and technology.

3D structural and petrophysical modeling of Qishn sandstone reservoir in Sharyoof field, Say'un-Masilah basin, Yemen

The complex geological structures, of the Sharyoof field in the Say'un-Masilah Basin of Yemen, make obtaining accurate information about the hydrocarbon entrapment style difficult. This situation adversely affects the efficiency of the exploration. Therefore, the present study provides a detailed character analysis of subsurface structural features as well as determines the entrapment style of Early Cretaceous age hydrocarbons (the Qishn Sandstone Reservoir) in the Sharyoof oil field. To identify accurate structural features, calculate petrophysical parameters of the Qishn sandstone member and predict their complex geometry in a 3D model, this investigation is based on the analysis of a multidisciplinary data set. The three-dimensional modeling was based on the interpretation of 2D seismic profiles and well logs data analysis. The obtained results indicate two types of a normal faults, consisting of plane faults and antithetic faults, which are oriented NE-SW and NW-SE with a thickness variation from 76 to 153 m. The intersection of these faults resulted in horst structures, in the northwest and southwestern parts, and graben and half-graben structures, in the southern and southeastern parts of the study area. The dips of these faults are between 20 and 90°. The 3D models of petrophysical parameters and the cross section extracted from the 3D model demonstrated that the Qishn sandstone reservoir has a low clay volume while having high porosity, permeability and hydrocarbon saturation values. Furthermore, the Qishn Sandstone is overlain by layers of the Qishn Carbonate Member, which has very low porosity and permeability and high clay volume, making it an effective seal. Therefore, these novel findings could be used to propose a drilling site for exploration wells within the Qishn Clastics membership.

Fluid Substitution-Based Reservoir Studies and Seismic Response in ‘Vyshion’ Field, Niger Delta

A case study of how fluid substitution affects the seismic waveforms is presented. Direct hydrocarbon prediction on the seismic data is prone to inaccuracy without investigating the impact of fluids on the seismic waveforms since the seismic data is influenced by mineral composition, porosity, salinity, pressure, and other factors in addition to fluid type. The study relies on 3D seismic data and log data gathered from 3 wells. Petrophysical and rock physics models were computed in order to understand the seismic dataset. In the analysis, prolific hydrocarbon intervals were identified. Then, model compressional velocities and densities obtained for various fluid scenarios were generated by using the Gassmann fluid substitution theory. Normalized bulk modulus approach was used to reduce the ambiguities that shales portend on the velocity models. Model synthetics were generated. The synthetic seismograms were compared with the seismic dataset in order to understand how fluid saturation and lithology impacts the seismic data. In the analysis, two major hydrocarbon bearing reservoirs were delineated. Other mapped reservoirs have characteristic indices that make them unsuitable for the fluid modelling. The results show that the model oil velocity model better approximates the field velocity. The density models produced the same kind of results, suggesting that the reservoir fluid is oil. The generated synthetic diagrams show that replacing the in-situ fluid with either gas or oil models has no appreciable impact on the seismic dataset’s amplitude waveform. This is because seismic reflection amplitude only slightly increases each time gas is assumed. By using the seismic data from this field of study, hydrocarbons cannot be directly predicted from amplitude anomalies because the lithology better influences the seismic waveforms than the fluid composition.

Geological Modelling of Sandstones Formations and Petrophysical Characterization of Hydrocarbon Reservoirs in the Termit Basin, Eastern Niger: Case of the Goumeri Prospect

The general objective of this study, which focuses on the geological modelling of sandstone formations and petrophysical characterization of hydrocarbon reservoirs in the Termit basin, is to build a geological model to visualize the geometry of reservoir formations. Its specific objectives are: (1) determine the extension of promising reservoir formations, (2) establish models of petrophysical parameters (porosity, permeability and saturation). The methodology implemented is based on the integration of lithological data and petrographic parameters from the logs into the Petrel software. The interpretation of the results obtained on geological modelling shows; geometry and extension of reservoir formations in the form of sand lenses of varying thickness from one prospect to another. Petrophysical parameter models including porosity and permeability models have made it possible to understand the vertical distribution of the different reservoir units.

Massive Spatial Well Clustering Based on Conventional Well Log Feature Extraction for Fast Formation Heterogeneity Characterization

Abstract Recent enhancements in computational capacity provide an opportunity for harnessing the enormous amount of reservoir data already acquired and extracting useful information for hydrocarbon exploration, development, and production. This article reports a three-step clustering technique to determine well groups based on subsurface geological heterogeneity using feature extraction, hierarchical ensemble clustering, and spatial mapping. The first step of the presented methodology is to group the wells into different clusters based on the formation rock composition and property features extracted from well logs using the expectation maximization algorithm. The one-dimensional (1D) stacking pattern of each well log curve is expressed through a two-dimensional (2D) transformation scheme. Thus, the clustering can capture the vertical stacking patterns of well logs, which is essential for reservoir heterogeneity characterization. This base clustering process generated a feature matrix which is further grouped through the hierarchical ensemble clustering in a latent space of well logs in the second step. Through the ensemble clustering, different clustering proposals obtained from the base clustering are integrated corroboratively to reflect a comprehensive feature of all studied logs. In the third step, the spatial clustering is performed based on the ensemble results, considering the spatial distances between well locations in the target area. The results of the 2D spatial map may provide insights into the sedimentary depositional environment in terms of the lateral geological heterogeneity features. Therefore, the proposed clustering technique can present a fast geological modeling method to integrate geological heterogeneity features presented in multiple well logs, which is not yet fully utilized in traditional geomodeling approaches. The results can also support further reservoir studies, such as petrophysical modeling, reservoir modeling, and fluid flow simulation studies.

Hydraulic fracturing as unconventional production potential for the organic-rich carbonate reservoir rocks in the Abu El Gharadig Field, north western Desert (Egypt): Evidence from combined organic geochemical, petrophysical and bulk kinetics modeling results

This paper systematically analyzes the organic geochemical, petrophysical, and petrographical properties combined with bulk kinetics modeling of the Abu Roash (F) organic-rich carbonate rocks in the Abu El Gharadig Field. The Abu Roash (F) carbonate-rich samples exhibit high organic content with total organic matter (TOC) values up to 3.04 wt%, and mainly Type II kerogen, with a slight gradient to Type II/III and III kerogens, reaching good to very good oil generation potential. This finding of hydrogen-rich kerogen and oil generation potential was also demonstrated by the abundance of fluorescent alginite, amorphous organic matter (AOM), and bituminite organic matter (OM) as established via ultra violet (UV) light microscopy. The maturity indicators demonstrate that most of the examined Abu Roash (F) carbonate-rich samples from the studied wells, with a deep burial depth of more than 3000 m, are thermally mature, thus defining an early mature to moderate-mature stage. The kinetic models suggest that the Abu Roash (F) carbonate-rich rocks in the deepest burial depth, with calculated vitrinite reflectance (%VRo) values in the range of 0.72–0.83 %, have reached kerogen transformation ratio (TR) in the range of 10–55 %, indicating a high probability of oil production. This finding is confirmed by the presence of the oil crossover in these rocks with an oil saturation index (OSI) of more than 100 mg HC/ g rock. The Abu Roash (F) organic-rich carbonates are intractable rocks as implied by low porosities (up to 2.33 %) and poor permeability in the range of 0.0017–0.0039 mD. The pores in these rocks have a wide range in size, including interparticle, fracture, and organic matter (OM) pores, as recognized in the thin section and scanning electron microscopy (SEM). The development of these pore types and their quality is mainly controlled by high mineralogical brittleness (i.e., carbonates) together with the high OM inputs. Based on the above characteristics, the Abu Roash (F) carbonate-rich rocks in the Abu El Gharadig Field are a candidate for unconventional tight oil reservoir potential, which typically require a form of hydraulic fracturing for possible oil production at deeper burial depths.

Reconstruction of petrophysical zoning of the Blagodatnoye gold deposit in the Yenisei Ridge: Geodynamic and physical-chemical aspect

Research subject. Petrophysical zoning of the Blagodatnoye gold-sulfide deposit in the Yenisei Ridge. Aim. To determine indicative petrophysical characteristics of the products of the main occurrence stages and to develop an evolutionary petrophysical model of the investigated deposit.Materials and methods. Physical fields were studied by the methods of magnetic and electrical exploration and gamma-spectrometry. The petromagnetic heterogeneity and mineralogical-geo chemical features of formation of polymetamorphic complexes, metasomatites and ores were studied by a neutron activation analysis of the content of rare earth and radioactive elements, petrochemical x-ray fluorescence analysis, as well as by an electron-probe microanalysis of pyrite.Results. The syncollisional fold-overthrust fault (785 Ma) of the preparatory stage provided structural control over the ore-bearing mineral-forming system. The signs of zone dislocation metamorphism include geophysical anomalies: magnetic and natural electrical anomalies due to pyrrhotite and graphite mineralization of cleavage zones on fold limbs, and specific electrical resistance from silicification zones in fold hinges. The metasomatism of the pre-ore (753 Ma) and ore (698 Ma) stages took place under rifting conditions. Pre-ore quartz-muscovite and chlorite metasomatites with carbon mineralization and supra-background Au concentrations were formed under the action of reducing reaction solutions; they remained unaltered in the non-productive part of the deposit. These formations are characterized by elevated concentrations of radioactive elements and natural electrochemical polarizability. During the ore stage, Au was concentrated by fluids with hydro-carbonate-sulfide composition under the violation of the strike-slip kinematics, which caused significant petrophysical transformations of the productive part of the deposit. Early carbon metasomatites in the sub-ore and root sections of the ore bodies were depleted in terms of U, at the same time as retaining their electrochemical activity. Uranium accumulated in the upper horizons of the productive part, whose rocks lost their polarizability due to scattered carbonate mineralization. Magnetic pyrrhotite crystallized as part of sulfides with a regular increase in its proportion in the root sections of the ore bodies. At the final stage (368 Ma), the mineralized zone was broken into a series of blocks with unequal vertical displacements and levels of erosional truncation by upcasts. This led to the exposure of various-depth sections with contrast petrophysical characteristics.Conclusions. The Blagodatnoye deposit was formed in four stages: preparatory, two ore-generating and final. The petrophysical features of the products of each stage formed the basis for the developed evolutionary petrophysical model, which will be tested on the materials of geophysical studies of the Yenisei Ridge territories.

Complex Resistivity Anisotropy Response Characteristics of Wufeng-Longmaxi Formation Shale in Southern Sichuan

Electrical exploration has become an important means of shale gas reservoir exploration and evaluation, and is expected to play a key role in the later stages of reservoir fracturing and development. At present, the research on the electrical response characteristics of shale gas reservoirs and their relationship with reservoir parameters is extensive and in-depth, but there is little research on their complex resistivity anisotropy characteristics and influencing factors, which restricts petrophysical modeling and reservoir parameter prediction, and reduces the reliability of shale gas exploration and reservoir evaluation by electromagnetic methods. In this paper, shale samples from the Longmaxi Formation and the Wufeng Formation of shale gas wells in southern Sichuan were collected, the complex resistivity of 34 shales in bedding direction and vertical bedding direction were measured, and the induced polarization (IP) parameters of shales were extracted by inversion. The electrical anisotropy response characteristics under different temperature and pressure conditions were analyzed, and the influencing factors and laws of complex resistivity anisotropy of shales were revealed. Combined with the test results of shale porosity and permeability, the evaluation model of resistivity, polarizability and porosity and permeability parameters was established. The research results have formed a set of testing methods and analysis techniques for electrical anisotropy of shale reservoirs, which are mainly based on complex resistivity parameter testing. It is helpful to understand the electrical anisotropy characteristics of shale gas reservoirs in southern Sichuan; this will provide the theoretical and physical basis for shale gas reservoir evaluation and fracturing monitoring by electrical exploration.

Stochastic inversion of tracer test data with seismicity constraint for permeability imaging in enhanced geothermal reservoirs

Inference of permeability distribution in an enhanced geothermal reservoir is crucial for the sustainable management of geothermal energy. However, interpreting the uneven permeability distribution in a deep geothermal reservoir remains a challenging task because in practice there often are merely one or two wells available for hydrogeophysical tests. Considering that the induced seismicity data are widely captured during reservoir stimulation in enhanced geothermal systems, a framework of tracer test data inversion with the constraint of induced seismic data is developed for permeability imaging. Hydraulic diffusivity, representing the prior estimation of permeability, is inferred from the occurrence time of seismic events. This is followed by the determination of a petrophysical model, which relates hydraulic diffusivity to permeability, by tracer test data inversion based on the Markov chain Monte Carlo algorithm. Implementation of the seismicity-constraint tracer data inversion algorithm in the Habanero enhanced geothermal system, Australia, demonstrates that our inversion model allows uneven permeability estimation at field scale in shorter burn-in period and lower uncertainty than the traditional inversion model without seismicity constraint. Using the estimated permeability in the hydrothermal model enables accurate prediction of thermal performance in a 150 day trial-production test. Results indicate that this algorithm can reliably characterize the spatial distribution of permeability in deep enhanced reservoirs, based on the tracer test via doublet wells.

Building 3D geological model using non-uniform gridding for Mishrif reservoir in Garraf oilfield

Mishrif formation is the main carbonate reservoir in southern Iraq, which is extremely heterogeneous and require accurate geological description for optimal oil field development. This research is associated with developing a representative 3D static model that conserves geological elements and relieves the uncertainty of reservoir properties and volumetric estimates. The interpreted log data and core reports were selected to capture all structural, stratigraphical and petrophysical properties. The reservoir is discretized with irregular cells using the tartan grid, concentrating their accuracy in important areas. A sequential Gaussian simulation algorithm distributed the petrophysical properties for all reservoir units. The structural model showed that Mishrif reservoir in Garraf oil field has a domal structure with two main producing reservoirs (M1.2 and L1.2). The petrophysical model results present that unit L1.2 has high-quality properties with average porosity of 0.24 and water saturation of 0.17 and less than in unit M1.2, where the average water saturation and porosity are 0.47 and 0.185, respectively. The estimated oil in place with the volumetric method was 901 Million standard cubic meters, most of which accumulated in unit L1.2. This study was applied to reappraise the reserves of Mishrif reservoir in Garraf oil field using irregular gridding.

Petrophysical Regression regarding Porosity, Permeability, and Water Saturation Driven by Logging-Based Ensemble and Transfer Learnings: A Case Study of Sandy-Mud Reservoirs

From a general review, most petrophysical models applied for the conventional logging interpretation imply that porosity, permeability, or water saturation mathematically have a linear or nonlinear relationship with well logs, and then arguing the prediction of these three parameters actually is accessible under a regression of logging sequences. Based on this knowledge, ensemble learning technique, partially developed for fitting problems, can be regarded as a solution. Light gradient boosting machine (LightGBM) is proved as one representative of the state-of-the-art ensemble learning, thus adopted as a potential solver to predict three target reservoir characters. To guarantee the predicting quality of LightGBM, continuous restricted Boltzmann machine (CRBM) and Bayesian optimization (Bayes) are introduced as assistants to enhance the significance of input logs and the setting of employed hyperparameters. Thereby, a new hybrid predictor, named CRBM-Bayes-LightGBM, is proposed for the prediction task. To validate the working performance of the proposed predictor, the basic data derived from the member of Chang 8, Jiyuan Oilfield, Ordos Basin, Northern China, is collected to launch the corresponding experiments. Additionally, to highlight the validating effect, three sophisticated predictors, including k-nearest neighbors (KNN), support vector regression (SVR), and random forest (RF), are introduced as competitors to implement a contrast. Since ensemble learning models universally will cause an underfitting issue when dealing with a small-volumetric dataset, transfer learning in this circumstance will be employed as an aided technique for the core predictor to achieve a satisfactory prediction. Then, three experiments are purposefully designed for four validated predictors, and given a comprehensive analysis of the gained experimented results, two critical points are concluded: (1) compared to three competitors, LightGBM-cored predictor has capability to produce more reliable predicted results, and the reliability can be further improved under a usage of more learning samples; (2) transfer learning is really functional in completing a satisfactory prediction for a small-volumetric dataset and furthermore has access to perform better when serving for the proposed predictor. Consequently, CRBM-Bayes-LightGBM combined with transfer learning is solidly demonstrated by a stronger capability and an expected robustness on the prediction of porosity, permeability, and water saturation, which then clarify that the proposed predictor can be viewed as a preferential selection when geologists, geophysicists, or petrophysicists need to finalize a characterization of sandy-mud reservoirs.

Acoustic logging response law in shales based on petrophysical model

Shale acoustic logging response law is complex due to the multiple minerals and pores, which limits the application of acoustic logging in shale reservoir parameter evaluation, therefore clarifying the shale acoustic logging response law is of great importance. Different petrophysical models are adopted for the equivalence of organic matter, clay, matrix minerals, and fractures, in Wufeng-Longmaxi shale formation in the Jiaoshiba area. Finally, the self-consistent approximation model is used to combine different components, and a shale petrophysical model with a complex pore structure is constructed. The model verification results show it has good predictability for shale. Based on the model, the effect of different mineral compositions and different types of pores are studied. The results show that: 1) The effect of clay and organic matter is very complex, and the variation laws of layered clay (organic matter) and dispersed clay (organic matter) on the acoustic wave are consistent. 2) Layered clay or organic matter leads to the formation anisotropy increase, which makes the acoustic time difference greater than that of containing dispersed clay (organic matter). 3) The fracture is the main control factor of anisotropy, and the anisotropy of gas-bearing fracture is higher than that of water/oil fracture.

Improving moisture content estimation from field resistivity measurements with subsurface structure information

• Smoothness constraint in regularized resistivity inversion is removed at structural boundaries. • Structural unit-specific petrophysical models are used for moisture interpretation. • Moisture content is better estimated from resistivity with the new method. In Earth sciences, the measurement of soil and rock moisture content is essential in improving our understanding of various hydrologic processes. Recently, the electrical resistivity method has been frequently used to estimate the moisture content in the field. The uncertainty associated with resistivity-estimated moisture content is mainly from two sources: regularized inversion and petrophysical interpretation. In this study, to reduce the uncertainty, we propose (1) to use subsurface structural information from seismic refraction measurements to relax the smoothness-based regularization at structural boundaries and (2) to use structural unit-specific petrophysical relationships to translate resistivity into moisture content. The proposed methods are tested on a synthetic subsurface model featuring three distinct layers of a granitic critical zone (CZ). The results of the synthetic example show that both the spatial pattern and the moisture content values estimated with the new method are very close to the true model with low uncertainty. Compared to the traditional method, the estimation is significantly improved, particularly at the CZ boundaries, such as the regolith-fractured bedrock interface. We also apply the new method to a granitic hillslope to estimate the moisture content distribution from field resistivity measurements. Although no ground truth is available for validation, the estimated moisture content distributions exhibit some typical hydrological features in hillslopes, such as the perched water at the soil/rock interface and preferential flow path in fractured rocks. Therefore, it is concluded that incorporating structural information in resistivity inversion and using structural unit-specific petrophysical models can improve moisture content estimation from field resistivity measurements.

Petrophysical Modeling of Domanic Rocks as a Basis of Seismic Data Interpretation

Petrophysical Modeling of Domanic Rocks as a Basis of Seismic Data Interpretation

Three-dimensional petrophysical models by the quality cha- racteristics and filtration properties of reservoirs (in the context of Sangachal-Duvanny-Khara-Zira adasi field)

The paper presents the methods of estimation of quality and filtration characteristics of the reservoirs – quality index of layers (QIL) and indicator of flow zone (IFZ). With the purpose of the specification of QIL and IFZ parameters through the well sections, the dependences using core sample analysis and the parameters obtained with the methods of well logging have been developed. Three-dimensional petrophysical models and more detailed cross-sectional profiles by QIL and IFZ parameters allowing highlighting the areas with better reservoir properties of the studied field have been developed using estimated parameters..

Calibrated petrophysical model for elevated organic matter intervals and mineralogical variability in the Agrio Formation, Neuquén Basin, Argentina

Organic carbon-bearing mudstone units of variable lithologies exhibit complex internal heterogeneities in total organic carbon (TOC) enrichment and mineralogy related to stratigraphic and geographic variability. Elevated organic matter-bearing intervals within unconventional reservoirs are commonly contained within these thick (100's of meters), low TOC mudstone units, but poorly delineated. The Cretaceous Agrio Formation is a mixed siliciclastic-carbonate mudstone, known source rock unit, and an emerging unconventional play in the hydrocarbon-rich Neuquén Basin of Argentina with internal and geographic heterogeneity. Source rock intervals within the formation have been identified from a detailed outcrop study; however, the variability of hydrocarbon source rock quality and mineralogy of the unconventional reservoir target intervals in the subsurface is relatively unconstrained. A published petrophysical model for a bimodal clay-silica system was modified to predict intervals of elevated organic matter and ternary clay-silica-carbonate mineralogical compositional trends for distinguishing mudstone complexity in the Agrio Formation. This study uniquely distinguishes carbonate-rich from silica-rich mudstone log response across the paleodepositional profile of the system. The calibrated petrophysical model utilized cuttings programmed pyrolysis and mineralogical XRD data applied to wireline well logs from the southern Mendoza and central Neuquén provinces. Predicted logs were used to correlate elevated organic matter distribution, mineralogical composition, and assess stratigraphic and geographic heterogeneity. Thirteen log-derived elevated organic matter-bearing intervals (wireline TOC >1.25 wt%) were identified using the modified petrophysical model, expanding on the previously interpreted five outcrop source intervals in the Agrio Formation. Organic richness thickness and abundance increases in the northern Neuquén to southern Mendoza province within the study area. The new petrophysical workflow can be applied to improve unconventional target decisions for hydrocarbon exploration efficiency in mudstones worldwide.

Characterization of the Giant Chicontepec Tight Oil Paleochannel in Mexico and Integration with Actual Cumulative Oil Production

Summary The Chicontepec paleochannel contains unconventional tight oil shaly sandstone reservoirs also characterized by natural fractures of tectonic origin. Chicontepec ranks as a giant reservoir with volumes of original oil in place (OOIP) ranging between 137,300 and 59,000 million STB (Guzman 2019). Although the cumulative oil is significant (440.38 million STB), it only represents 0.32 to 0.75% of the OOIP. The objective of this study is to develop a new characterization methodology with a view to increase oil recovery from Chicontepec. OOIP in Chicontepec paleochannels was estimated originally at 137,300 million STB. Despite several studies using state-of-the-art methodologies and contracting major oilfield services companies to test new technologies and significant investments, the OOIP was decreased recently to 59,000 million STB due to lack of any significant success on the implemented projects. This study shows that the key to success is understanding the contribution of natural fractures. This is demonstrated for the case of Chicontepec with a new dual-porosity petrophysical model for naturally fractured laminar shaly sandstone reservoirs developed in this study. The model assumes that matrix and fractures are in parallel. Laminar shaliness is handled with a parameter (Alam) that is a function of true and shale resistivities, and fractional shale volume (Vsh). The methodology integrates data from observations in outcrops, quantitative evaluation of cores, well logs, and actual production data. Past Chicontepec studies have assumed that the porosity exponent (m) in Archie and shaly sandstone equations is constant. However, core studies indicate that Chicontepec m values become smaller as porosity decreases. The proposed dual-porosity petrophysical model, when applied to actual Chicontepec wells, matches properly the laboratory values of m and generates results that generally compare well with actual production data (e.g., the larger the value of fracture partitioning, the larger is the cumulative oil production). Pattern recognition allows estimating fracture intensity with a partitioning coefficient, which is calculated as the ratio of fracture porosity to total porosity. The new contribution of this manuscript is the development of a petrophysical dual-porosity model for naturally fractured shaly sandstone reservoirs that integrates variable values of m from cores, fracture intensity, and cumulative production of individual Chicontepec wells. Our detailed review of the literature indicates that this methodology has not been published previously.

Application of induced polarization imaging across different scales to understand surface and groundwater flow at the Hofermuehle landslide

Understanding changes in hydraulic properties of the subsurface is critical to delineate areas susceptible for groundwater accumulation and the triggering of landslides. Laboratory studies have demonstrated the possibility to estimate the hydraulic conductivity from induced polarization (IP) measurements. However, to-date only rare studies have been applied at the field scale and none has evaluated the frequency-dependence in field IP imaging data. We show that the application of petrophysical models linking hydraulic conductivity (K) and IP at 1 Hz, resolves for the same estimations from frequency-domain measurements as well as from time-domain IP. Moreover, our IP images reveal an evident frequency-dependence between 0.1 and 240 Hz in the electrical properties, which is also observed in lab measurements conducted in soil samples. To account for this, we fit a Cole-Cole model to our multi-frequency IP results and evaluate models linking K and the normalized chargeability, gaining a subsurface model of the hydraulic conductivity with enhanced resolution. Our results reveal clear variations at depth in the electrical conductivity and polarization associated with the presence of a plane of instability and the sliding plane. We also resolve lateral changes delineating areas with K below 10-6 m/s, which may act as barriers for groundwater flow. To evaluate our results we also estimate the hydraulic conductivity using a joint inversion algorithm that directly solves for porosity and saturation through the simultaneous inversion of seismic refraction and electrical resistivity tomography data. We observed consistent hydraulic conductivity images obtained through the inversion of the IP data and the joint inversion, with such model being in agreement with existing information of the site. We resolve a 3D model of the hydraulic conductivity at the Hofermuehle landslide from IP data that reveals the geometry of areas with poor drainage that may lead to land sliding.