Abstract: Compositions and methods according to the invention are directed to a cement composition for use in a subterranean formation. The cement composition comprises: (A) cement; (B) water; and (C) a polymer, wherein the polymer: (i) comprises a monomer or monomers selected from the group consisting of epoxysuccinic acid, a substituted epoxysuccinic acid, and an alkali metal salt, alkaline earth metal salt, or ammonium salt of any of the foregoing, and any combination of any of the foregoing; (ii) has the following characteristics: (a) is water soluble; and (b) is biodegradable; and (iii) is capable of providing: (a) a thickening time of at least 2 hours for a test composition at a temperature of 190° F. and a pressure of 5,160 psi; and (b) an initial setting time of less than 24 hours for the test composition at a temperature of 217° F. and a pressure of 3,000 psi, wherein the test composition consists of 860 grams of Class-H Portland cement, 325 grams of deionized water, and 0.

Abstract: Provided herein are methods and compositions that include a method comprising contacting a metal surface with an acidic fluid comprising a corrosion inhibitor that comprises a reaction product formed from a direct or an indirect reaction of an aldehyde with a thiol and/or an amine functionalized ring structure. A composition provided includes an acidic treatment fluid that comprises an aqueous-base fluid, and acid, and a corrosion inhibitor that comprises a reaction product formed from a direct or an indirect reaction of an aldehyde with a thiol and/or an amine functionalized ring structure.

Abstract: An artificial neural network, ANN, and method of training the ANN for inversion of logging tool signals into well logs of formation parameters is disclosed. Properly selected synthetic models of earth formations are used to train the ANN. The models include Oklahoma and chirp type of formations. In each model parameter contrasts of from 10 to 1 to about 100 to 1 are included. Models including maximum and minimum parameter values spanning the operating range of the selected logging tool are included. Parameter contrasts at interfaces are limited to realistic values found in earth formations. The selected models are used to generate synthetic tool signals, which are then used as inputs to the ANN for training. When the ANN coefficients are properly adjusted to produce an output matching the original models, the ANN can be used for inversion of any real signals from the selected logging tool.

Abstract: The acoustic isolator assembly of the present invention comprises a elongated cylindrical body suited for connection to an acoustic array and subsequent disposition within a wellbore. According to one embodiment of the present invention, the acoustic isolator comprises a plurality of cylindrical isolator modules that are coaxially arranged to form the body of the tool. Each isolator module comprises a spring disposed within an outer housing. The separate isolator modules are attached to one another by connecting rods around which are disposed a plurality of metal spacers. The isolator module further comprises mechanical stops that limit the deflection of the spring during high axial loading. These features enable the acoustic isolator assembly to withstand the high loading that may be applied during logging operations. Therefore, the isolator modules are capable of supporting high compressive and tensile loads without suffering permanent deformation of the springs.