Pore Pressure Estimation Research Articles

Application of the Vernik method for pore-pressure estimation in the Vaca Muerta Formation: Insights for geomechanical analysis and quantitative seismic interpretation in organic-rich mudrocks

Application of the Vernik method for pore-pressure estimation in the Vaca Muerta Formation: Insights for geomechanical analysis and quantitative seismic interpretation in organic-rich mudrocks

Estimating pore pressure in tight sandstone gas reservoirs: A comprehensive approach integrating rock physics models and deep neural networks

Pore pressure serves as an important driving power for subsurface fluid migration and therefore has a significant impact on gas accumulation and enrichment in tight sandstone reservoirs. Tight gas is typically produced in overpressure regions, where pressure coefficients are notably elevated. Thus, it is crucial to establish an effective methodology for precise pore pressure estimation. This study introduces an approach to improve pore pressure prediction by incorporating rock physical modeling and deep neural networks (DNNs) into the classical Eaton method. Compared to conventional techniques relying on empirical correlations between pressure coefficients and elastic properties, the proposed method considers the influence of porosity, fluids, and lithology, which could enhance reliability in pore pressure prediction. Meanwhile, a prediction model is developed using logging data and DNNs to estimate mineralogical volumetric fractions based on elastic properties. This prediction model allows improved estimation of rock matrix elastic properties using seismic-inverted data, which is crucial for estimating normal compaction velocity to extend pore pressure prediction from individual boreholes to the whole study area. Real data applications demonstrate that the predicted pressure coefficients derived from seismic data using the method presented in this paper align well with the gas enrichment estimated in previous studies for the tight sandstone reservoirs. Furthermore, regions with high values of pressure coefficients correspond to high gas content. These findings validate the effectiveness of the proposed methodology, which can provide valuable insights for identifying potential tight sandstone reservoirs.

BRIEF UNDERSTANDING OF CHARACTERISTICS DEPLETED RESERVOIR (INTERVAL-I) USING PORE PRESSURE AND FRACTURE GRADIENT ANALYSIS IN "X" FIELD, SANGA-SANGA AXIS, KUTAI BASIN

Field X, as this study area's focus, boasts over 200 wells proven to be hydrocarbon producers. Two pore pressure regimes exist: normal hydrostatic and overpressure. The primary hydrocarbon reservoir in the Balikpapan Formation within the Sanga- sanga axis at Field X consists of sandstone. Drilling disturbances, particularly in the lower intervals of this reservoir, often occur due to overpressure. The main challenge encountered in this reservoir is mud losses. The objective of this study is to develop the Pore Pressure and Fracture Gradient characteristics and its relation to the geological environment. Furthermore, the distribution of Sand (Interval-I) is determined, which is the primary cause of losses due to production. Besides that, the parameters used to create optimal fracture gradient is also defined. Thirteen wells in this field were examined to identify the controlling factors of pore pressure. This study integrates wireline logging, velocity, mud logs, pressure tests, drilling parameters and event which are subsequently processed for determining shale points, Normal Compaction Trend (NCT), calculating overburden gradient, and estimating pore pressure using the Eaton method. From the analysis result, the distribution of overpressure and the generating mechanism of overpressure are determined. This study also carried out analysis to determine overpressure and depleted Sandstone (Interval-I) distribution. Subsequently, facies and depositional environtment analysis are conducted, followed by modelling Sandstone (Interval-I) and determining Sandstone’s poisson ratio from loss data and shale’s from leak of test data for fracture gradient estimation. Overpressure is found in Interval-I with magnitude of 4000-4700 psi, which corresponds to delta plain to delta front depositional environment. Top of overpressure is observed shallower in the southern than northern due to geological structure conditions. The generating mechanism of overpressure is caused by loading and hydrocarbon generation. The experienced loss in overpressure zone, caused by reservoir production from the initial pressure of 4475 psi and has depleted to 373 psi. From the sandstone distribution model, the loss sandstones are a connected fluvial channel in southern ward. It is also observed several unconnected channel sandstones that did not experience loss. Poisson ratio parameter for sandstone is 0.35, which is calibrated from the loss event with minimum fracture gradient in Interval-I is approximately 4772 psi. It is expected that the understanding of pore pressure and Sandstone (Interval-I) distribution could be used to increase the success ratio for optimal drilling planning, including to choose effective casing design, mud weight, and appropriate total depth.

Assessment of Sealing Potential of Fault-Bounded Hydrocarbon Prospect in Gabo Field, Niger Delta, Nigeria

Sealing potentials of faults are an important exploration risk to consider in the assessment of fault-bounded hydrocarbon prospects. This technique has been used for predicting potential hydrocarbon columns for mitigating risk in exploration and appraisals. Hence, the objective of the paper is to assess the sealing potential of the fault-bounded hydrocarbon prospects of the Gabo Field in the Niger Delta basin using seismic, well-log, and X-ray diffraction data. Three faults were interpreted as normal and syn-depositional faults. The well-log correlation showed that the shale sequence was inter-bedded with sands and showed a good spread with a relative thickness ranging between 12-105m from shallow to intermediate depth intervals. Results of the rock property analysis showed that the volume of shale ranged from 18 – 73.72% with an average of 63.59%. The total porosity ranged from 15.9 – 31.7 (good to excellent) with an average of 16.7 (good) in the shales and 27.2 (very good) in the sand. The effective porosity of the field ranged from 3.58 – 22.71 with an average of 6.028 in the shales and 20.13 in the sand. The estimated pore pressure ranged from 42.13 – 47.62psi with an average of 47.0psi in the shales and 42.8psi in the sand. The results of the X-ray diffraction analysis showed that the predominant minerals were kaolinite, rutile, gypsum, albite, microcline and quartz, which constitute the caprock sequence and the faulted rocks. Results of the sealing potential showed poor sealing in the shale sequence while the fault analysis showed good sealing along the fault planes. These results deduced the sealing uncertainty of the field and may be applied to similar siliciclastic trap configurations in deltaic environments.

Impact of disequilibrium compaction and unloading on overpressure in the southern Junggar Foreland Basin, NW China

Disequilibrium compaction caused by burial or tectonic compression and unloading are the common overpressure mechanisms in foreland basins. However, accurately identifying multiple overpressure origins in such basins is challenging, since it requires distinguishing impact of vertical and horizontal stresses on compaction and overpressure as well as identifying overpressure caused by unloading. This paper proposed a dual compaction factor method (DCFM) to address these issues. A basic DCFM schematic diagram was established through analyzing compaction behaviors before and after tectonic compression to distinguish overpressure derived from two types of disequilibrium compaction and overpressure induced by unloading. In DCFM, a compaction model for mudstone in the foreland basin, which was only controlled by burial, was established based on the relationship between mean deposition rate and compaction factor in weak tectonic compression zone (WTCZ). It was used to determine compaction factor, normal compaction trend (NCT), acoustic transit time, bulk density, and overburden pressure under this compaction condition, as well as to distinguish the impact of burial and tectonic compression on porosity and overpressure at strong tectonic compression zone (STCZ). The DCFM employs mean stress to revise the equivalent depth method (EDM). Pore pressures associated with compaction only derived from burial and derived from both burial and tectonic compression were estimated using conventional EDM and revised EDM, respectively. The total pore pressures were estimated using the Eaton method and were calibrated based on measured ones. Overpressure associated with unloading was determined by comparing total pore pressure with estimated pore pressure generated with disequilibrium compaction. This mode was further applied at two wells from the Sikeshu Sag in the southern Junggar Foreland Basin to reconstruct accurate overpressure profiles with multiple origins, which were consistent with measured pressures and matched well with geological characteristics. Disequilibrium compaction induced by tectonic compression and burial is responsible for overpressure at the Sikeshu Sag. Overpressure transfer is also one of the primary contributors to the excess pressure in the Jurassic and Cretaceous in the Gaoquan anticline at the Sikeshu Sag, with a maximum contribution of 38 %. Plays, consisting of sandstone reservoirs with both transferred overpressure and tectonic-induced overpressure as well as mudstone caprocks with overpressure due to disequilibrium compaction, are favorable for hydrocarbon accumulation. This study can quantify the impact of overpressures with multiple origins on hydrocarbon migration and sealing capacity of caprocks, as well as provide ideas for researching fluid evolution in sedimentary basins.

Stress‐induced anisotropy in Gulf of Mexico sandstones and the prediction of in situ stress

AbstractThe strong sensitivity of velocity to stress observed in many sandstones originates from the response of stress‐sensitive discontinuities such as grain contacts and microcracks to a change in effective stress. If the change in stress is anisotropic, then the change in elastic wave velocities will also be anisotropic. Characterization of stress‐induced elastic anisotropy in sandstones may enable estimation of the in situ three dimensional stress tensor with important application in solving problems occurring during drilling, such as borehole instability, and during production, such as sanding and reservoir compaction. Other applications include designing hydraulic fracture stimulations and quantifying production‐induced stresses which may lead to rock failure. Current methods for estimating stress anisotropy from acoustic anisotropy rely on third‐order elasticity, which ignores rock microstructure and gives elastic moduli that vary linearly with strain. Elastic stiffnesses in sandstones vary non‐linearly with stress. Using P‐ and S‐wave velocities measured on Gulf of Mexico sandstones, this non‐linearity is found to be consistent with a micromechanical model in which the discontinuities are represented by stress‐dependent normal and shear compliances. Stress‐induced anisotropy increases with increasing stress anisotropy at small stress but then decreases at larger stresses as the discontinuities close and their compliance decreases. When the ratio of normal‐to‐shear compliance of the discontinuities is unity, the stress‐induced anisotropy is elliptical, but for values different from unity, the stress‐induced anisotropy becomes anelliptic. Although vertical stress can be obtained by integrating the formation's bulk density from the surface to the depth of interest, and minimum horizontal stress can be estimated using leak‐off tests or hydraulic fracture data, maximum horizontal stress is more difficult to estimate. Maximum horizontal stress is overpredicted based on third‐order elasticity using measured shear moduli, with estimates of pore pressure, vertical stress and minimum horizontal stress as input. The non‐linear response of grain contacts and microcracks to stress must be considered to improve such estimates.

Analyzing in situ stresses and wellbore stability in one of the south Iranian hydrocarbon gas reservoirs

This study aims to analyze in situ stresses and wellbore stability in one of the Iranian gas reservoirs by using well log data, including density, sonic (compressional and shear slowness), porosity, formation micro-image (FMI) logs, modular formation dynamics tester (MDT), and rock mechanical tests. The high burial depth, high pore pressure, and strike-slip stress regime of the field require an optimal design of geomechanical parameters based on an integrated data set consisting of static and dynamic data, which is available for this study. Firstly, poroelastic modulus and vertical stress were calculated. Afterward, the Eaton’s equation was used to estimate pore pressure from well logging data. The geomechanical parameters were also calibrated through the interpretation of image data, the use of the modular formation dynamics tester (MDT), and laboratory rock mechanic tests. Employing poroelastic equations, the lowest and highest horizontal stresses were calculated. It was shown that the maximum horizontal stress and minimum horizontal stress correspond to sigma H and sigma h, indicating the strike-slope fault regime. The findings of this research indicated that the equivalent mud weight (EMW) resulted in 10–13 ppg suitable for the Kangan Formation and 11–14 ppg suitable for the Dalan Formation. Additionally, the well azimuth in the NE-SW direction provided the best stability for drilling the encountered formations. Therefore, the results of this study serve as cost-effective tools in planning adjacent wells in carbonate formations of gas field to predict the wellbore stability and safe mud window.

Rock physics and basin modeling nexus for predicting pore pressure

Improving accuracy in pre-drill pore pressure predictions is a fundamental starting point for well design including setting boundaries for casing points and mud weights. Although rock physics modeling is used routinely in pore pressure estimates, existing rock physics modeling approaches have been largely empirical and face challenges to predict pore pressure accurately, especially for deeper drilling targets where rock matrix properties deviate from normal compaction trends, due to chemical alterations of the rocks. Moreover, existing rock physics models require petrophysical inversion for porosity and volume of shale. It is well-known that petrophysical inversion has non-uniqueness issues and creates additional uncertainty and inaccuracy in pore pressure prediction. Therefore, we developed an integrated modeling approach that involves rock physics modeling and physics-based basin modeling. Through fundamental rock physics modeling and in-depth understanding of the process of clay diagenesis, we recognize that the acoustic impedance from seismic inversions and level of organic metamorphism (LOM, as a proxy for thermal stress) estimated from basin modeling are critical for pore pressure prediction in mudrocks. Based on extensive post-drill data validation, we demonstrate that our modeling approach improves accuracy in pore pressure prediction for depth zones undergoing clay-diagenesis. In addition, we demonstrate that the integrated rock physics modeling greatly reduces the number of calibration parameters as needed in existing models. Blind tests of our method on well data in two different basins with drastically different burial history demonstrates the validity and generalizability of our approach.

ENHANCING PORE PRESSURE PREDICTION IN OIL WELL DRILLING: A COMPREHENSIVE STUDY OF WELL PLANNING AND COST-EFFECTIVE MODELING IN THE NIGER DELTA REGION

Accurate pore pressure prediction is pivotal in drilling operations, impacting safety, well design, and cost-effectiveness. This research paper aims to assess various pore pressure prediction methods, particularly in transition zones. It introduces a novel descriptive model for quick and reliable pore pressure estimation when essential data parameters are unavailable. The study underscores the importance of selecting appropriate prediction methods based on geological conditions. The research findings reveal that Eaton’s correlation utilizing transit compressive wave velocity offers superior pore pressure prediction when drilling through transition zones. Additionally, the developed descriptive model is a valuable tool for quick look pore pressure estimation, ensuring operational efficiency when data parameters for traditional methods like Eaton’s are lacking. However, a critical caveat emerges as the model’s suitability for pore pressure prediction in fractured or shaled-out reservoirs is questioned, necessitating caution in its application in such geological settings. This paper recommends the continued use of Eaton’s method as a reliable pore pressure prediction tool and advocates for the adoption of the proposed descriptive model in scenarios where time constraints or data limitations are prevalent. By amalgamating these approaches, drilling operations can achieve enhanced accuracy and efficiency in pore pressure assessment, ultimately contributing to safer and more cost-effective well-drilling processes.

Pore pressure prediction assisted by machine learning models combined with interpretations: A case study of an HTHP gas field, Yinggehai Basin

Accurately estimating pore pressure in high-temperature and high-pressure (HTHP) formations is crucial to prevent drilling problems and engineering disasters. In this study, four machine learning models were developed, namely decision tree, random forest, gradient boosting decision tree, and extreme boosting decision tree models, along with the classical Eaton's method, to rapidly predict pore pressure in an HTHP gas field in the Yinggehai Basin using seven variables, including ‘depth’ and six common well-logging series. The results demonstrate that the machine learning models outperform the classical Eaton's method in pore pressure prediction. Among the models, the decision tree model exhibits the best performance, with the highest correlation coefficient (R2 = 0.98) and the lowest root mean squared error (0.61). Additionally, the Graphviz tool and Shapley additive explanations method were used for the visualization and interpretation of the decision tree model to gain a deeper understanding of the model's working mechanism and the reasons behind the obtained results. The interpretation revealed that the variable of ‘depth’ was the most significant input parameter in the decision-making process of the model. This study provides insights into the ‘black-box’ interpretation of machine learning models and demonstrates that tree-based machine learning models can accurately predict pore pressure in undersurface HTHP formations.

Pore pressure prediction in offshore Niger delta using data-driven approach: Implications on drilling and reservoir quality

Despite exploration and production success in Niger Delta, several failed wells have been encountered due to overpressures. Hence, it is very essential to understand the spatial distribution of pore pressure and the generating mechanisms in order to mitigate the pitfalls that might arise during drilling. This research provides estimates of pore pressure along three offshore wells using the Eaton's transit time method, multi-layer perceptron artificial neural network (MLP-ANN) and random forest regression (RFR) algorithms. Our results show that there are three pressure magnitude regimes: normal pressure zone (hydrostatic pressure), transition pressure zone (slightly above hydrostatic pressure), and over pressured zone (significantly above hydrostatic pressure). The top of the geopressured zone (2873 mbRT or 9425.853 ft) averagely marks the onset of overpressurization with the excess pore pressure above hydrostatic pressure (P∗) varying averagely along the three wells between 1.06−24.75 MPa. The results from the three methods are self-consistent with strong correlation between the Eaton's method and the two machine learning models. The models have high accuracy of about > 97%, low mean absolute percentage error (MAPE < 3%) and coefficient of determination (R2> 0.98). Our results have also shown that the principal generating mechanisms responsible for high pore pressure in the offshore Niger Delta are disequilibrium compaction, unloading (fluid expansion) and shale diagenesis.

Estimation of pore pressure considering hydrocarbon generation pressurization using Bayesian inversion

Undercompaction and hydrocarbon generation are the main factors affecting pore pressure. The current seismic pore-pressure prediction (PPP) method is to obtain the overpressure trend by estimating the normal compaction trend (NCT) to predict the physical parameters during normal compaction and comparing the measured parameters. However, selecting a single parameter to indicate overpressure may cause insufficient consideration of factors, such as hydrocarbon generation. Because hydrocarbon generation requires specific temperature and other conditions, pore pressure is divided into two parts: undercompaction in the early stage and hydrocarbon generation after reaching the hydrocarbon generation threshold. A rock-physical model is established for estimating the NCT before hydrocarbon generation to modify the bulk modulus of the model and calculate the pressure generated by undercompaction; the pressure generated by hydrocarbon generation is added to obtain the final pore pressure. In the shale gas work area in the Sichuan Basin, the prediction results are more in line with the actual situation, and the petrophysical analysis indicates that the ratio of free hydrocarbon content and kerogen to water is the influencing factor indicating pore pressure. The practicality of the PPP formula considering hydrocarbon generation in oil and gas sweet spots is illustrated through an example in the research area.

ANN-based estimation of pore pressure of hydrocarbon reservoirs—a case study

ANN-based estimation of pore pressure of hydrocarbon reservoirs—a case study

Rock physics model for velocity—pressure relations and its application to shale pore pressure estimation

Acoustic wave velocity has been commonly utilized to predict subsurface geopressure using empirical relations. Acoustic wave velocity is, however, affected by many factors. To estimate pore pressure accurately, we here propose to use elastic rock physics models to understand and analyze quantitatively the various contributions from these different factors affecting wave velocity. We report a closed-form relationship between the frame flexibility factor (γ) in a rock physics model and differential pressure, which presents the major control of pressure on elastic properties such as bulk modulus and compressional wave velocity. For a gas-bearing shale with abundant micro-cracks and fractures, its bulk modulus is much lower at abnormally high pore pressure (high γ values) where thin cracks and flat pores are open than that at normal hydrostatic pressure (low γ values) where pores are more rounded on average. The developed relations between bulk modulus and differential pressure have been successfully applied to the Upper Ordovician Wufeng and Lower Silurian Longmaxi formations in the Dingshan area of the Sichuan Basin to map the three-dimensional spatial distribution of pore pressure in the shale, integrating core, log and seismic data. The estimated results agree well with field measurements. Pressure coefficient is positively correlated to gas content. The relations and methods reported here could be useful for hydrocarbon exploration, production, and drilling safety in both unconventional and conventional fields.

Assessment of reservoir stress state and its implications for Paleozoic tight oil reservoir development in the Oued Mya Basin, northeastern Algerian Sahara

• In-situ stress regime and pore pressure of the tight Paleozoic reservoirs. • A mean NW-SE S HMax orientation inferred from the B-D quality wellbore breakouts. • Multiple linear regression models to predict the S hmin and S HMax magnitudes. • Estimated pore pressure and in-situ stress behavior agree with observed data. • Optimum drilling and stimulation strategies are inferred. The Cambrian and Ordovician clastic reservoirs of the Oued Mya Basin exhibit significant vertical thickness and extensive lateral continuity, despite being tight. These reservoir intervals have not been properly understood yet in terms of in-situ stress distribution and pore pressure behaviour. The main objectives were to infer the reservoir stress state and draw implications for the tight oil reservoir development based on the geomechanical analyses. We interpreted breakouts from a cumulative 1485 m of acoustic image logs and interpreted a NW-SE S HMax orientation (N125°E-N147°E) in the Oued Mya Basin. The inferred breakouts were of B-D quality as per the World Stress Map ranking criteria. Both the reservoirs have a pore pressure gradient of 13.58-13.77 MPa/km, while the minifrac data infers a reservoir S hmin gradient of 17.3-19.2 MPa/km. Based on the breakout widths, we estimated the S HMax gradient as 23.8-26.5 MPa/km. Following the univariate regression analyses to identify various influencing parameters on horizontal stress magnitudes, we proposed multiple linear regression (MLR) models to predict the S hmin and S HMax based on pore pressure, S v , Poisson's ratio, and Young's modulus. Results indicate that S v influences the horizontal stress estimates significantly more as compared to the other influencing variables. The predicted S hmin and S HMax values are in good agreement (goodness of fit as R 2 = 0.976 and 0.994) with the measured data. The newly proposed MLR equations can be utilized in absence of subsurface validation data. A strike-slip faulting reservoir stress state is concluded from stress polygon analysis. An optimum drilling strategy is discussed based on the observed wellbore failures. We recommended the drilling fluid pressure to be increased by 8 MPa and 14 MPa to avoid breakouts against the Ordovician and Cambrian reservoirs respectively, however, that may incur tensile fractures which do not have a considerable effect on wellbore stability while drilling. Based on this work, horizontal well trajectory along NE-SW (i.e., parallel to S hmin ), together with oriented perforations aligned parallel to inferred S HMax direction is recommended. The potential fracture reactivation risks during reservoir pressurization are evaluated and discussed.

Anisotropic Poroelastic Modelling of Depletion-Induced Pore Pressure Changes in Valhall Overburden

Stress and pore pressure changes due to depletion of or injection into a reservoir are key elements in stability analysis of overburden shales. However, the undrained pore pressure response in shales is often neglected but needs to be considered because of their low permeability. Due to the anisotropic nature of shales, the orientation of both rock and stresses should be considered. To account for misalignment of the medium and the stress tensor, we used anisotropic poroelasticity theory to derive an angle-dependent expression for the pore pressure changes in transversely isotropic media under true-triaxial stress conditions. We experimentally estimated poroelastic pore pressure parameters of a shale from the Lista formation at the Valhall field. We combined the experimental results with finite element modelling to estimate the pore pressure development in the Valhall overburden over a period of nearly 40 years. The results indicate non-negligible pore pressure changes several hundred meters above the reservoir, as well as significant differences between pore pressure and effective stress estimates obtained using isotropic and anisotropic pore pressure parameters. We formulate a simple model approximating the undrained pore pressure response in low permeable overburden. Our results suggest that in the proximity of the reservoir the amplitude of the undrained pore pressure changes may be comparable to effective stresses. Combined with the findings of joint analysis of locations of casing deformation and total and effective stresses, the results suggest that pore pressure modelling may become an important element of casing collapse and caprock failure risk analysis and mitigation.

Pore Pressure Estimation for Shaly Sand Formations Using Rock Physics Models For Compressional and Shear Velocities: A 1D Geomechanical Approach

Pore pressure estimation in sedimentary basins has been made exclusively through the compressional velocity data since the 1960s, using the normal compaction trend and lithostatic pressure profile derived from wireline logs. Considering that seismic velocity is highly dependent on petrophysical parameters such as porosity and clay volume, pore pressure estimation is commonly associated with a high degree of uncertainty due to simplistic assumptions that neglect those dependencies. To improve that, we propose two empirical velocity models based on compressional and shear rock physics relations for pore pressure prediction in shaly sand formations. These formulations extend Bowers and Doyen formulae, linking compressional and shear velocities with effective stress and petrophysical parameters. Finally, we used a non-linear multidimensional inversion approach to calibrate the proposed models and apply them in the context of a 1D geomechanics and pore pressure prediction study of an upper cretaceous overpressured shaly sand oil reservoir. The results show good agreement with pore pressure data and pressure predictions from the traditional Eaton method. The advantage of the proposed approach is its consistency throughout the entire well-log petrophysical interpretation workflow, especially concerning porosity, clay volume and saturation.

Screening of future carbon storage sites – selecting the best spots

Subsurface carbon storage can occur in depleted oil and gas fields, in water-wet structures, or in open aquifers. All three types of storage sites present advantages and inconveniences, which will be reviewed in this talk. The selection of future sites for carbon storage balances storage capacity (how much CO2 can be stored), injectivity (how efficiently or fast CO2 can be stored), and containment risk (how safely CO2 can be stored). We present a rigorous uncertainty-based approach involving estimates of pore volume, pressure and temperature conditions and resulting fluid properties, and sealing and containment behaviour, to highlight areas with best potential for safe and effective carbon storage.

The identification of normal to underpressured formations in the Southeastern Sichuan basin

The Sichuan Basin contains many overpressured formations with pore pressure coefficients as high as 2.3. However, in a Nanye 1 well found in the Southeastern (SE) Sichuan Basin, low-pore pressure coefficients as low as 0.9 have been recorded at a depth between 1544.3 and 1903.6 m, indicating the presence of underpressured formations. But the knowledge of normal and underpressured formations is not well studied in the SE Sichuan Basin. In this work, the normal to underpressured formations in the SE Sichuan Basin are identified, and their origins are discussed.We integrated the pore pressure measurement and estimation, pore pressure coefficient and pore pressure depth plot to identify the normal to underpressured formations. We also integrated basin modelling along with the faults system to determine the origins of underpressured formations. As a result, the Upper Permian Longtan and Middle Permian Maokou Formations (1906.5–2782.9 m depth) in the Nanchuan area, were identified as normal-to-underpressured gas deposits. Also, the study identified the Lower Silurian Longmaxi and Upper Ordovician Wufeng Formations (2072–2160 m depth) in the Pengshui area, SE of the Chongqing region as normal pressured gas formations. The study discovered a decrease in temperature, rock porosity rebound and gas migration out of the formations through faults as the reasons for underpressured formations in this area. The tectonic uplift and erosion resulted in a decrease in temperature and rebound of the rock porosity, which contributed to total pore pressure drop up to 46.62 MPa. The tight overlying seal rocks and underlying rocks helped to sustain the low pore pressures in these formations.

Technology Focus: Offshore Drilling and Completion (October 2022)

Big data, in its many forms, has promised much to the oil and gas industry but mostly is perceived to have been slow to deliver. This is not at all surprising. We must walk before we can run, and, as experience has grown with the nuances and successful and unsuccessful avenues of investigation, the industry has continued to move forward. As the saying goes, “Data is like people: Interrogate it hard enough and it will tell you whatever you want to hear.” From early and almost naïve beginnings, where systems would confidently predict that Friday followed Thursday, we entered a phase where data mining began to provide insight. Often these insights confirmed long-established relationships; for example, in hydraulic fracturing, more than once I have seen heavily marketed research and development that professes to predict the onset of screenout conditions only to see that the system has effectively “seen” a Nolte-Smith relationship. These, however, are mere stumbles of any system picking itself up and beginning to move, and should be expected. What we have seen are continued areas of application opening up, where approaches deliver real efficiency gains and highlight further opportunities. The papers that I included this month fall into these categories, demonstrating real measurable efficiency gains and advantages, often processing volumes of data that previously could not be managed by conventional means. Performance measurement and drilling automation are two such examples, and the papers referenced this month, both as synopses and listed for further reading, fall into this category. Not surprisingly, as we apply data science to broader problem sets across the industry, we will see continued development and demonstrated success. Sharing these successes will ensure that this momentum is sustained and that advances continue. Recommended additional reading at OnePetro: www.onepetro.org. IPTC 21419 - Delivering More Fit-for-Purpose Wells With Low-Cost Approach at Untapped Area Matured Field—Application of Cone Concept Statistical Approach by M. Hatta M. Yusof, Petronas, et al. IPTC 21490 - Pore-Pressure Estimation by Using Machine-Learning Model by Pichita Booncharoen, Chevron, et al. SPE 209712 - Drilling Control System Automation To Control Axial Velocity Optimizes Tripping and Drilling Performance by Robert Bacon, Sekal, et al.