Interactive Analysis (IRA) is a new reservoir study method which applies to both condensate oil & gas reservoir and conventional oil & gas reservoir. IRA establishes the correspondence between stage EUR equivalents and reservoir parameters. Often, reservoir parameters include but not limited to porosity, permeability, burst pressure, Poisson rate, Oil saturation or Gas content, Free gas content and adsorption gas content, pay zone thickness, resistivity, mud content, etc. In a specific compartmentalization, it is important to decide which parameter is the focal parameter dominating the productivity. If the focal parameters can be decided, operators can use this evidence to decide which zone and which sub-zone drilling must fully penetrate through. Additional, when well is designed for hydraulic fracturing, engineers can use this data to design stages and clusters. Designing of higher focal parameter quality in stage and cluster is certainly a contribution to better frac efficiency and EUR. IRA is expressed that the Normalized Correlated Coefficient (NCC) Vector is equal to the Moore-Penrose inverse of the Normalized Reservoir Parameter Quality Factors (NRPQF) matrix multiplying the Normalized EUR equivalent (NEE) vector. NCC deriving from the IRA represents the weight of productivity contribution to EUR. Analyzing IRA equation, the focal parameters dominating the well EUR can be determined. With focal parameters available, operators can optimize the drilling criteria and optimize frac design. For a specific compartmentalization, the focal parameters derived from IRA shall give consistent focal parameters which dominate the higher productivity and lower productivity. When a well is hydraulic fractured, the NEE can be tested and analyzed. To input the NEE into IRA equation, the frac efficiency is also reflected by NEE. Three shale gas wells in a compartmentalization are analyzed via IRA analysis. The positive focal parameters, irrelevant parameters and negative focal parameters in each well and overall averaging give good convergence. Two wells in condensate oil pay zone in a compartmentalization are also analyzed via IRA analysis. The positive focal parameters, irrelevant parameters and negative focal parameters in each well and overall averaging give some convergence. If a NCC is bigger, it dominates EUR. If it is small or very small, the contribution to EUR is less or measily. On the other hand, if a NCC is positive, it increases the productivity when the parameter quality is higher. If a NCC is negative, it decreases the productivity when the parameter quality is higher. No focal parameter dominating EUR can be understood until IRA is proposed. Rather than reservoir mechanics analysis, IRA gives explicit linear mathematical expression which makes engineers easier to calculate by aid of Matlab coding. IRA analysis is a breakthrough to understand the intrinsic structure between reservoir parameters and EUR.

Billions of dollars are invested into hydraulic fracturing every year. However, how to optimize frac design parameters such as stage and cluster spacing, fluid and proppant volume into each stage, number of perforations per cluster and temporary isolation is still not clear. This paper proposes a new method to estimate the volume of proppant penetrating each perforation hole. By aid of high-resolution optical imaging technology, perforation hole size before and after frac treatment can be accurately measured and interpreted. The difference in area before and after Frac is the eroded perforation area. Eroded area represents the sand entry into a perforation. Sand Entry Distribution (SED) determines the frac efficiency. Better SED gives better frac efficiency. Operators understand that different frac treatment volumes and different cluster versus perforation holes designs will impact the productivity. With the technology proposed in this paper, different frac designs can be measured and calculated using SED. A better SED in a cluster and/or a stage is certainly a better frac design. The method described in this paper estimates the proppant volume penetrating into each perforation hole after frac. Furthermore, a number of statistics and comparison between clusters and stages are described in the paper to give operators a clear indication of which frac design gives better frac efficiency and more uniform distribution.

It is a great challenge for well integrity when a high volume gas production well is found with the production casing broken near the wellhead hanger resulting in high pressure communication between Annulus A and B. The objective of the paper is to propose a new solution to establish a strong pressure barrier between annulus via a sealant system and to show that such a barrier has been proven to be durable for long time. A proprietary resin sealant is the key technology and precise job planning and execution are also viewed as being vital to the success of treatments. Because tubing flow pressure may reach up to 10,000 psi during production after recompletion, operator decided to pressure test the sealant barrier to 10,000 psi for a minimum of 30 minutes duration. If pressure drop during the pressure test is less than 100psi, then the well is allowed to be recompleted. Several spots and squeezes of sealant eventually setup a strong pressure barrier and were pressure tested up to 10,000 psi in both A and B Annuli. There was no pressure communication at the other annulus in the 30 minute test period. In the past six (6) years, the operator has tried several jobs to repair casing leaks but none were successful. It was the first time that a sealant system provided a solution to repair a casing leak and hold a high pressure differential. During recompletion, the production packer failed to set but the operator decided to initiate production. A annulus pressure increased quickly and finally stabilized at 8700 psi. It is now a year since the job was completed in October, 2019, and B annulus pressure in has consistently remained at zero pressure. This has proved that the sealant technology can securely setup and provide a high pressure barrier which is valid for long term V0 sealing.

Find & Plug is defined as locating water zone in either vertical or horizontal well and shut it off. The most challenging job in a horizontal completion well is to locate the water producing zone, especially after a period of production over time. Once the water producing zone is precisely located, either mechanical or chemical isolation can be deployed to shut the zone off. PLT and donwhole monitoring such as fiber optical and downhole gauge are common technologies to locate the water zone. PLT log is somewhat risky and/or questionable to determine zones production profile when well relies on sucker rod for production or horizontal completed. Data is only for 6-12 hours duration which may not reflect the dynamic change of reservoir water influx. Fiber Optics can only measure zone pressure and temperature. To achieve the production profile, a mathematical model must be setup. Many parameters in the model are estimated and therefore the calculation or simulation of water producing downhole is overall questionable. Permanent gauges have to be deployed attaching onto tubing or casing. Wire has to go down to production zones thru the tubing or casing. It will take some rig time and is costly to deploy. This paper proposed a new model using polymer tracer to deploy with tubing alongside the production zones, either vertical or horizontal, with or without packers for isolation of each zone, to measure the liquid profile of interest zones at initial production and water profile of interest zones over a period of production. By deploying the polymer tracers near the production zones, the tracer sub will be installed atop or below the zones depending on where the ICV is located. When liquid and water produced from each zone, it must pass through the tracer sub where the tracers will dissolve into the produced water at initial stage and diffuse into produced water after the dissolution process is almost saturated. Surface samples of liquid and water will be taken by a designed sampling program and sent to lab for analysis. Analysis data will be interpreted by SHANIP and SHANWC model. SHANIP model is a mathematical formula which establishes relationship between produced tracers and zone liquid concentration at initial production. SHANWC model is a mathematical formula which establishes relationship between produced tracers and zone water concentration after the dissolution process is almost terminated. If packers are installed between interest zones to isolate the zonal production, SHANIP and SHANWC model can quantitative measure each zone liquid production and water concentration over a period of production. The period can be 6 months, 1 year or even longer depending on the amount of tracers installed and volume of water producing. If no packers are isolated between interest zones, a qualitative analysis to zonal water cut can be achieved. Those include major water producing zones, no production zones, low water cut zones, etc. With SHANIP and SHANWC models, clients and researchers in O&G can easily and economically evaluate the zones water cut at any time they wish. And no intervention is necessary except for the first tubing deployment.

Understanding interwell connectivity is crucial for EOR decision making. In 1990, K.N Wood et al proposed a method to evaluate the interwell Residual Oil using a reactive tracer and a non-partition tracer. A decade later in 2001 (Joseph Tang, 2001), Joseph Tang et al proposed a method to identify the single well near bore residual oil saturation by puff and huff approach in a single well carbonate reservoir. Today the interwell connectivity is still under research. The objective of this paper is to propose latest study to evaluate interwell connectivity through two or more partitioning tracers to estimate the breakthrough, pore volume, sweeping channel geometry, high permeability channel, residual oil saturation, etc Thanks to the new development in tracer technologies, today we can use two distinctive tracers to pump through injection well and collect tracers produced in all production wells. The different partition coefficients for two tracers can reveal the lag factor for the sweeping channel and further derive the statistical channel breakthrough time, pore volume, geometry, tortuosity and residual oil saturation. The theory, derivation and applications of the concepts are described in this paper. Based on the analysis, sweeping channels statistical information can be calculated by a simple mathematical expression of the ratio of two distinctive tracer mass produced from production wells, the ratio of two tracer dynamic partitioning coefficients and the ratio of two injected tracer mass. With this information, operator can investigate a compartmentalization in the field to optimize flooding plan. One 9-piont injection well grid were analyzed, and results are shown in this paper. Those results are important input to operators' reservoir model. It revealed the major sweeping channels and azimuths, the major residual oil channel and their azimuths, the possible tortuous channels and their azimuths which gives operator a direction of where the residual oil resides and how easy or difficult it can be recovered in tertiary oil production. This new theory analyzes sweeping channel statistical information from produced masses of two distinctively partitioning tracers, which follows a rigorous mathematical derivation and setup a volume factor equation relating to produced masses of two partitioning tracers. The partitioning coefficient is also modified by a dynamic factor to better simulate the moving partition in channel rather than the static partitioning between brine and oil.