Unlocking Growth Opportunities Through Saturation Evaluation Behind Complex Completion by Applying State-of-Art Pulsed Neutron Technology

Perseverance in quantifying the remaining hydrocarbon saturation, in cased boreholes, remains critical to take business decisions and prioritize operations in brownfield waterflood development. Challenges with cased hole saturation evaluation acquired in certain complex completions such as those completed in multiple casing-tubing strings, slotted-liners and sand-screens require advanced tool technology. Pulsed Neutron Logging (PNL) is one such technology used successfully to analyze behind casing saturation evaluation. The PNL device provide accurate and precise measurement, and with robust processing and environmental compensation corrections, the saturation uncertainty can be delineated. A robust cased hole hydrocarbon saturation and uncertainty estimation enables informed decision making and value driven workover prioritization. The new generation PNL tool features a high-output electronic neutron source and four signal detectors. Near and far Gamma Ray (GR) detectors are made of Cerium-doped Lanthanum Bromide (LaBr3: Ce) featuring high-count rate efficiency and high-spectral resolution (largely insensitive to temperatures variations). A deep-reading GR detector made of Yttrium Aluminum Perovskite (YAP) in combination with a compact fast neutron monitor placed adjacent to the neutron source, enables a new measurement of the fast neutron cross section (FNXS) which provides sensitivity to gas-filled porosity. A newly devised pulsing scheme allows simultaneous measurement in both time and energy domains. The time-domain measurement aid in analyzing the self-compensated capture cross section (SIGM), neutron porosity (TPHI), and FNXS. The energy-domain measurement provides a detailed insight for high-precision mineralogy, total organic carbon (TOC), and carbon/oxygen ratio (COR). The high statistical precision energy-domain capture and inelastic spectral yield data are interpreted using an oxide-closure model which when combined with an extensive tool characterization database provide lithology and saturation measurements compensated for wellbore and completion contributions. This paper shares the advanced features of the new multi-detector PNL tool run in a horizontal well targeting the aeolian Mahwis Formation, consisting of unconsolidated sands and the glacial Al Khlata Formation (Porosity ranges 0.25 – 0.29 p.u.). In this case-study, the well was completed with uncemented sand screens and production tubing to mitigate sanding related risk. The absence of cement behind casing and the presence of screens adds considerable complexity to the saturation analysis. Furthermore, due to low water salinity (∼7000 ppm NaCl equivalent), saturation must be determined using carbon spectroscopy-based techniques - namely the COR and TOC. Logging conventional PNL tools in horizontal wells can lead to lengthy acquisition times, thus adding considerable operational complexity and cost. With the new PNL technology advancements, the time required to acquire high-quality data can be halved. Saturation outputs computed independently from COR and TOC methods showed close agreement and allowed for the direct compensation of changes in borehole oil hold-up without which the computed saturation would have been overestimated. The remaining oil saturation estimation behind cased hole and uncertainty quantification enable a proper understanding of well production performance and uncovered further opportunities. In addition, decision based strategic data acquisition to quantify remaining hydrocarbon saturation enables unlocking growth and ‘no further action’ (NFA) opportunities, impacting production recovery and meeting bottom-line targets in brownfield assets.

Exploiting Slim Pulsed Neutron Spectroscopy for Unlocking Reservoir Potential in Brownfields: Two Examples from Gulf of Suez Offshore Field in Egypt

For more than 40 years, pulsed neutron spectroscopy has been primarily used in reservoir management to determine hydrocarbon saturation profiles, tracking reservoir depletion, and planning workover activities to diagnose production problems such as water influx. Legacy pulsed neutron tools used to provide this information for more than four decades, but they were challenged when a mixed lithology reservoir is encountered, complex completions, unknown borehole conditions, and poor cement integrity in cased boreholes. This paper presents two successful field examples and applications using the advanced slim pulsed neutron spectroscopy to precisely determine multiphase contacts in a complex geological structure, provide current hydrocarbon saturation independent of the quality of cement behind the casing, and identifying bypassed hydrocarbon. This was of paramount importance in understanding current reservoir fluid distribution to reveal the true potential of this offshore brownfield located in the Gulf of Suez, Egypt. An integrated approach and candidate well selection were done that resulted in selecting two candidate wells that had poor cement quality behind casing, heterogeneous carbonate reservoir with mixed lithology, and uncertain fluid contacts in a complex reservoir structure. These combined borehole and reservoir conditions resemble challenges for capturing this crucial information with high confidence using the legacy pulsed neutron tool, and therefore required an advanced technology that can overcome these challenges using a single logging mode at twice the logging speed of any current pulsed neutron technology available in the industry. Based on the results, a workover campaign was implemented in this mature field to increase overall oil production with very efficient cost control, especially with this unprecedented time the O&G industry is going through. An integrated approach was set that resulted in the selection of two wells for the saturation determination logging tool deployment. Detailed high-resolution mineralogy, self-compensated total porosity and sigma, fluid type identification, and multiphase fluid saturation was obtained with high precision behind cased borehole independent of cement integrity and borehole fluid reinvasion. The results provided crucial information as an input to the integrated reservoir engineering approach which revealed around a 100-m net oil interval which was previously overlooked due to relatively low resistivity. Besides, fluids contacts were evaluated that confirmed the development of a secondary gas cap and the water encroachment direction. This technology can be further applied to more brownfields provided the right candidate selection is done to understand the potentiality of the field which would increase the recovery factor of the brownfields that represent almost more than 65% of the oil and gas fields around the world.

Petrophysical evaluation of sandstone gas reservoir using integrated well logs and core data for the Lower Cretaceous Kharita formation, Western Desert, Egypt

This study aims to evaluate Kharita gas reservoir to enhance the production. The increase in water-cut ratio reduces the left hydrocarbons’ amount behind pipe. Accurate determination of pore throats, pores connectivity and fluid distribution are central elements in improved reservoir description. The integration of core and logging data responses is often used to draw inferences about lithology, depositional sequences, facies, and fluid content. These inferences are based on petrophysical models utilizing correlations among tools’ responses as well as rocks and fluids properties. Upper Kharita Formation produces gas and condensate from the clastic sandstone in Badr-3 field, western desert of Egypt. It consists mainly of sandstone with shale intercalations. It is subdivided into three sub-units Kharita A, Kharita B and Kharita C that are in pressure communication. Hence, a new further investigation and review for the previously calculated GIIP (gas initially in place) was initiated. The results of this study yielded that the main uncertainty in the volumetric calculations was the petrophysical evaluation; subsequently, a new unconventional petrophysical evaluation approach was performed. The sands thickness in Upper Kharita Formation varies between more than 9 up and more than 61 m with average porosity values range between 0.08 and 0.17 PU while the average permeability values range between 1.89 and 696.66 mD. The average hydrocarbon saturation values range between 46 and 97%. The sands thickness in Upper Kharita Formation varies between more than 9 up and more than 61 m with average porosity values range between 0.08 and 0.17 PU while the average permeability values range between 1.89 and 696.66 mD. The average hydrocarbon saturation values range between 46 and 97%. Reservoir shale cutoff of 55% by using cross-plot between shale volume and porosity (Toby Darling concept) was utilized to discriminate the reservoir from non-reservoir sections. The porosity model was used to calculate reservoir porosity, using the density log. The Archie and saturation/height function models were used to calculate the water saturation and used to calibrate the water saturation in the transition zone. The porosity–permeability (POR-PERM) transform equation was used to estimate the reservoir connectivity (absolute permeability) for the four petrophysical facies (High Quality Reservoir, Moderate Quality Reservoir, Low Quality Reservoir and Highly Shale Reservoir). Core data have shown variations in reservoir quality parameters (porosity and permeability) from one well to the other. Integration of all the reservoir pressures indicated that there are different fluid types (oil, gas and water) in the Upper Kharita Formation level. The saturation/height function model was used to calibrate the saturation in the transition zone. The integration of geological core and geophysical log data helped to conduct a comprehensive petrophysical assessment of Upper Kharita Formation for a better estimation of the reservoir and to achieve a better understanding of the water encroachment in the Upper Kharita reservoir. The big challenge is the determination of the most correct model for calculating porosity, permeability and water saturation in this reservoir of different quality sand. The new petrophysical evaluation resulted in doubling the volumes in Upper Kharita reservoir and so a perforation campaign was performed to confirm the new volumetric calculations, which showed a good match with the model results. Hence, a new well was drilled targeting the low quality sand and found them with high pressure almost near virgin pressure.

Wykorzystanie technik sztucznych sieci neuronowych do predykcji wybranych parametrów jako uzupełnienia zbioru danych wejściowych w konstrukcji modeli parametrycznych 3D

The article presents the possibilities of using artificial neural networks for parametric prediction in borehole profiles, the application of which supplemented the set of information in all boreholes located within the analyzed area. The approach presented in the article will be used when there is no possibility of specialized interpretation of the drilling geophysics curves, supplementing the missing data. The set of data used in the study included solutions in the profiles of 10 boreholes, four of which were characterized by the availability of the full data set analyzed in this article, including compressional wave velocity, effective porosity, hydrocarbon saturation, Young’s modulus and Poisson’s ratio. Using the technique of the operation of artificial neural networks, a prediction of missing information was carried out based on the relationships between the analyzed parameters in the wells, where the estimated data was available. In recent years, there has been a dynamic development of machine learning technology and the so-called artificial intelligence. There are very few fields of science in which they find no application. The hydrocarbon saturation parameter, despite the challenges posed by the interpretation of this parameter, was also subjected to an estimation attempt, confirming the low correlation values between the analyzed parameters and requiring much more advanced work of an individual nature. The results of parametric prediction, previously validated by characterizing the R and RMSE parameters, were applied in the next step in the spatial modeling process of all analyzed parameters. Finally, as part of the visualization of the differences between the use of an incomplete and partially estimated data set in spatial analysis, a map of mean values of the selected parameter within the analyzed interval was presented. The set of data prepared in this way allowed for a more reliable spatial reconstruction of the distribution of parameters important in the context of the characteristics of the hydrocarbon reservoir, on the basis of which, in the subsequent stages, it is possible to more fully assess the deposit potential of the analyzed object. The methodology presented in the article, supported by a real case study, is an alternative to geophysical interpretations that require financial and time resources, sometimes large numbers of boreholes, especially for areas characterized by relatively low spatial variability and tectonic complexity. The condition is the availability of the interpretation in at least several boreholes, constituting a pattern for recreating the variability of the tested parameter / parameters in the remaining profiles of the boreholes.

First LWD Co-Located Antenna Sensors for Real-Time Anisotropy and Dip Angle Determination, Yielding Better Look-Ahead Detection

Electromagnetic (EM) resistivity tools measure the electrical properties of downhole formations that are critical in determining the hydrocarbon saturation of a reservoir. In complex and heterogeneous reservoirs, both horizontal and vertical formation resistivities are required to obtain an accurate hydrocarbon saturation. For decades, wireline multicomponent induction type measurements have provided reliable determination of formation anisotropy, structural dip, and dip azimuth in wells with any orientation relative to the bedding planes. Logging-while-drilling (LWD) multi-array propagation resistivity tools have also demonstrated similar capability in deviated wells where the relative dip angle is between 45° and 90°. However, measuring anisotropy and dip in wells with a low relative dip angle still poses difficulties for LWD propagation resistivity systems because of the antenna structures employed. This paper describes the development of a new LWD EM sensor equipped with an innovative, co-located, tilted antenna structure. The tool, along with a unique processing scheme, enables the determination of horizontal and vertical resistivity as well as the dip angle and the azimuth of the formation based on an assumption of transversely isotropic (TI) formation models (Graciet and Shen, 1998) while drilling in real time. The co-located sensor design is capable of acquiring multicomponent signals that are sensitive to formation anisotropy and structural dip in wells at any orientation. Modeling studies and several field trials have proven that the design concept can detect these formation properties at any arbitrary wellbore deviation. This paper presents test results from the new technology, together with reference measurements from azimuthally compensated LWD and fully triaxial wireline resistivity measurements. A good comparison is observed in these trials, providing an independent verification of the tool performance. The azimuthal measurements of the new sensors allow for determining formation anisotropy and dip at any wellbore deviation (Bittar et al., 2011b; Bittar et al., 2012), as well as providing 360° azimuthal resistivity and geosignals and allowing a three-dimensional (3D) resistivity mapping technique for real-time decisions. Integrating the co-located antennas with deep-reading antennas in a near-bit collar further provides both anisotropy measurements and ultradeep signals very close to the bit and enhances look-ahead detection ranges for LWD applications.

MACRO-PORE HYDROCARBON SATURATION FROM NMR T1 - T2 MAPS IN THE UNCONVENTIONAL POINT-PLEASANT FORMATION

Of particular interest in unconventional reservoir characterization is an NMR log of total porosity and macro-pore hydrocarbon saturation, where both quantities are independent of a mineralogy model. A log of the macro-pore hydrocarbon saturation has a direct impact on calculating hydrocarbon reserves. It helps identify sweet spots in the reservoir to optimize horizontal-well placement for hydraulic fracturing and production. It also helps avoid water production which would negatively affect the economics of the well. However, NMR logs in unconventional shale are challenging due to potential overlapping signal in the 1-dimensional (1-D) 𝑇𝑇2 domain between micropore water and bound hydrocarbon (i.e. bitumen), and, macro-pore water and hydrocarbons. In response to this challenge, NMR core-analysis in unconventional organic-shale has proven that 2-dimensional (2-D) 𝑇𝑇1 − 𝑇𝑇2 correlation maps and the 𝑇𝑇1/𝑇𝑇2 ratio can be a powerful technique for fluid typing and saturation. One limitation is that these techniques often just compare fully hydrocarbon-saturated with fully brine-saturated cores to calibrate a set of cutoffs in 𝑇𝑇1, 𝑇𝑇2, and/or 𝑇𝑇1/𝑇𝑇2 ratio. These cutoffs are then blindly applied to 𝑇𝑇1 − 𝑇𝑇2 maps from logs or cores of unknown saturation to determine the macro-pore hydrocarbon saturation in the unconventional organic shale. An example from the unconventional Point-Pleasant formation is shown where the traditional 𝑇𝑇1 − 𝑇𝑇2 cutoff technique to determine macro-pore hydrocarbon saturation breaks down, which is remedied by measuring 𝑇𝑇1 − 𝑇𝑇2 maps on mixed hydrocarbon-water saturated cores. The results show that instead of using cutoffs, the log-mean 𝑇𝑇1 , log-mean 𝑇𝑇2 , and log-mean 𝑇𝑇1/𝑇𝑇2 ratio correlate strongly against macro-pore hydrocarbon saturation of the mixed-saturated cores. In particular, for the Point-Pleasant organic-shale formation, the log-mean 𝑇𝑇1 is much more sensitive to macro-pore hydrocarbon saturation than the log-mean 𝑇𝑇2 or log-mean 𝑇𝑇1/𝑇𝑇2 ratio. The calibration of macro-pore hydrocarbon saturation from log-mean 𝑇𝑇1 is found to be different above and below a para-sequence boundary (nonconformity) in the organic-shale interval, the results of which can be used to interpret NMR logs. Details of the time-efficient technique used to obtain the mixed hydrocarbon-water saturated cores are shown.

DECIPHERING LOW RESISTIVITY PAY TO DERISK A COMMERCIAL DISCOVERY: CASE STUDY FROM THE NORWEGIAN SEA

The Cretaceous Cape Vulture prospect (Norwegian Sea, Norway) consisted of three Cretaceous sand levels: Cape Vulture Lower, Main, and Upper. The prospect was drilled in 2017, targeting seismic amplitude anomalies that represented a combination of reservoir facies and hydrocarbons. As the first well (6608/10-17S) proved hydrocarbons down to base reservoir in Cape Vulture Main and Upper, an appraisal well with two sidetracks were planned and drilled to determine the reservoir development, pressure communication and oil-water contact. A good understanding of the lateral variation within the reservoir was of importance to the technical economical evaluation of the discovery. The appraisal wells planned for a comprehensive coring and logging program. The main objectives were to reduce the uncertainty of estimated in place volumes by establishing the depth of the hydrocarbon-water contact, prove lateral pressure communication within each reservoir level, reduce the uncertainty of lateral and vertical reservoir distribution and quality, reduce the uncertainty of hydrocarbon saturation and understand the relationship between seismic amplitude anomalies and subsurface properties / fluids. The logging program included triaxial resistivity, nuclear spectroscopy, electrical images, nuclear magnetic resonance (NMR) complementing triple combo, followed by formation pressure measurements, and fluid sampling. The presence of clay minerals in varying amounts within the reservoirs depresses the resistivity measurement and leads to underestimation of the hydrocarbon saturation when using conventional Archie’s equation - a common petrophysical challenge in such conditions. The hydrocarbon saturation is an important parameter when calculating reserves and estimating whether a discovery is of commercial value. Hence, reducing the uncertainty span on hydrocarbon saturation (total and effective) and estimating the net pay thickness is critical. Using core data and advanced down-hole measurements to optimize a resistivity-based saturation model can reduce the uncertainty of the saturation estimates. Here we document the petrophysical evaluation of the data acquired, assessing heterolithic low resistivity pay with wireline log measurements combined with core data. Focus on the coring strategy, recommendations on sampling intervals for the core analysis, and key logging measurement requirements. The results show substantial improvements in the understanding of the hydrocarbon saturation, ultimately increasing in-place volume estimates. The integrated analysis, including NMR measurements, helps to delineate the fluid contacts, further reducing the uncertainty on the recoverable net pay thickness. The core data validate the independent log-based laminated sand analysis. This illustrates how an integrated approach combining core measurements, logs, and formation testing provide an accurate evaluation of low resistivity pay reservoirs, reducing the uncertainty in the technical economical evaluation.

Evaluation of Petrophysical Parameters of Reservoir Sand Wells in Uzot-Field, Onshore Niger Delta Basin, Nigeria

Evaluation of the petrophysical parameters in Uzot-field was carried out using Well log data. The target for this study was the D3100 reservoir sand of wells Uz 004, Uz 005, U008 and Uz 011 with depth range of 5540ft to 5800ft across the four wells. Resistivity logs were used to identify hydrocarbon or water-bearing zones and hence indicate permeable zones while the various sand bodies were then identified using the gamma ray logs. The results showed the delineated reservoir units having porosity ranging from 21.40% to 33.80% indicating a suitable reservoir quality; permeability values from 1314md to 18089md attributed to the well sorted nature of the sands and hydrocarbon saturation range from 12.00% to 85.79% implying high hydrocarbon production. These results suggest a reservoir system whose performance is considered satisfactory for hydrocarbon production. Keywords: Petrophysical parameters, porosity, permeability, hydrocarbon saturation, Niger Delta Basin

Estimation of Initial Hydrocarbon Saturation Applying Machine Learning Under Petrophysical Uncertainty

Summary The initial hydrocarbon saturation has a major effect on field-development planning and resource estimation. However, the bases of the initial hydrocarbon saturation are indirect measurements from spatially distributed wells applying saturation-height modeling using uncertain parameters. Because of the multitude of parameters, applying assisted-matching methods requires trade-offs regarding the quality of objective functions used for the various observed data. Applying machine learning (ML) in a Bayesian framework helps overcome these challenges. In the present study, the methodology is used to derive posterior parameter distributions for saturation-height modeling honoring the petrophysical uncertainty in a field. The results are used for dynamic model initialization and will be applied for forecasting under uncertainty. To determine the dynamic numerical model initial hydrocarbon saturation, the saturation-height model (SHM) needs to be conditioned to the petrophysically interpreted logs. There were 2,500 geological realizations generated to cover the interpreted ranges of porosity, permeability, and saturations for 15 wells. For the SHM, 12 parameters and their ranges were introduced. Latin hypercube sampling was used to generate a training set for ML models using the random forest algorithm. The trained ML models were conditioned to the petrophysical log-derived saturation data. To ensure a fieldwide consistency of the dynamic numerical models, only parameter combinations honoring the interpreted saturation range for all wells were selected. The presented method allows for consistent initialization and for rejection of parameters that do not fit the observed data. In our case study, the most-significant observation concerns the posterior parameter-distribution ranges, which are narrowed down dramatically, such as the free-water-level (FWL) range, which is reduced from 645–670 m subsea level (mSS) to 656–668 mSS. Furthermore, the SHM parameters are proved independent; thus, the resulting posterior parameter ranges for the SHM can be used for conditioning production data to models and subsequent hydrocarbon-production forecasting. Additional observations can be made from the ML results, such as the correlation between wells; this allows for interpreting groups of wells that have a similar behavior, favor the same combinations, and potentially belong to the same compartment.