Reservoir Modeling of Carbonate on Fika Field: the Challenge to Capture the Complexity of Rock and Oil Types

DOI: 10.17014/ijog.v1i2.181The carbonate on Fika Field has a special character, because it grew above a basement high with the thickness and internal character variation. To develop the field, a proper geological model which can be used in reservoir simulation was needed. This model has to represent the complexity of the rock type and the variety of oil types among the clusters. Creating this model was challenging due to the heterogeneity of the Baturaja Formation (BRF): Early Miocene reef, carbonate platform, and breccia conglomerate grew up above the basement with a variety of thickness and quality distributions. The reservoir thickness varies between 23 - 600 ft and 3D seismic frequency ranges from 1 - 80 Hz with 25 Hz dominant frequency. Structurally, the Fika Field has a high basement slope, which has an impact on the flow unit layering slope. Based on production data, each area shows different characteristics and performance: some areas have high water cut and low cumulative production. Oil properties from several clusters also vary in wax content. The wax content can potentially build up a deposit inside tubing and flow-line, resulted in a possible disturbance to the operation. Five well cores were analyzed, including thin section and XRD. Seven check-shot data and 3D seismic Pre-Stack Time Migration (PSTM) were available with limited seismic resolution. A seismic analysis was done after well seismic tie was completed. This analysis included paleogeography, depth structure map, and distribution of reservoir and basement. Core and log data generated facies carbonate distribution and rock typing, defining properties for log analysis and permeability prediction for each zone. An Sw prediction for each well was created by J-function analysis. This elaborates capillary pressure from core data, so it is very similar to the real conditions. Different stages of the initial model were done i.e. scale-up properties, data analysis, variogram modeling, and then the properties were distributed using the geostatistic method. Finally, after G&G collaborated with petrophysicists and reservoir engineers to complete their integrated analysis, a geological model was finally created. After that, material balance was needed to confirm reserve calculations. The result of OOIP (Original Oil in Place) and OGIP (Original Gas in Place) were confirmed, because it was similar to the production data and reservoir pressure. The model was then ready to be used in reservoir simulation

2016 European Guidelines on cardiovascular disease prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of 10 societies and by invited experts)Developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR).

European Society of CardiologyThis is the author accepted manuscript. The final version is available from Oxford University Press via http://dx.doi.org/10.1093/eurheartj/ehw10

Prevalence of hidradenitis suppurativa

Importance Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease with a substantial burden. Standardized global prevalence estimates and data on associated sociodemographic and risk factors are lacking. Objective To estimate the global prevalence of HS and study differences in prevalence by age, sex, geographical location, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), smoking status, gross domestic product (GDP), and Human Development Index (HDI). Data Sources and Study Selection Included studies were conducted using the standardized Global Hidradenitis Suppurativa Atlas methodology with finalized data collection before May 19, 2023. Studies were required to use a population-based sampling method and conduct clinical confirmation of HS diagnosis following a screening questionnaire. Data Extraction and Synthesis Data were independently extracted from relevant studies by 2 reviewers (D.B. and C.E.M.) using a standardized form. Extracted variables included geographic location, age, sex, BMI (median and BMI >30), smoking status, HS prevalence estimates (with 95% CIs), GDP, and HDI. A proportional meta-analysis using a random-effects model was conducted on the included studies. Main Outcomes and Measures The primary outcome was the point prevalence of HS, confirmed by clinical examination. Secondary outcomes included differences in HS prevalence by sex, age, BMI category, smoking status, and country-level socioeconomic indicators (GDP and HDI). All outcomes were prespecified before data analysis. Results The sample included 22 743 participants, identifying 247 patients with HS, across 25 studies in 23 countries spanning 6 continents. The median proportion of female patients with HS was 55.6%, and the median age was 34.5 years. While the prevalence estimates showed considerable inconsistency (I2 > 75%; τ2 = 0.747), the overall random-effects global prevalence of HS was 0.99% (95% CI, 0.67%-1.46%). Female sex was the only factor observed to be associated with the prevalence estimates (β = 1.02; 95% CI, 1.01-1.03). Conclusions and Relevance In this meta-analysis, an estimated global prevalence of HS between 0.67% and 1.46% surpassed previous global estimates. Substantial global variations in HS prevalence were also observed. Female sex was the only factor associated with prevalence in this sample. Future studies assessing genetic, environmental, and etiological factors are warranted to explain the heterogeneity in prevalence